Modeling and simulation of naval radar scenarios using imported target data in Adapt MFR and v software release notes

Size: px
Start display at page:

Download "Modeling and simulation of naval radar scenarios using imported target data in Adapt MFR and v software release notes"

Transcription

1 Modeling and simulation of naval radar scenarios using imported target data in Adapt MFR and v software release notes Prepared by: B. Brinson and J. Chamberland C-CORE, 4043 Carling Ave., Suite 202, Ottawa, ON, K2K 2A4 Prepared for: Project Manager: Dr. Peter Moo Contract Number: W Contract Scientific Authority: Dr. Peter Moo The scientific or technical validity of this Contract Report is entirely the responsibility of the Contractor and the contents do not necessarily have the approval or endorsement of the Department of National Defence of Canada. Contract Report DRDC-RDDC-2017-C117 March 2017

2 c Her Majesty the Queen in Right of Canada as represented by the Minister of National Defence, 2017 c Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

3 Abstract This report summarizes the work done under Task 8 of Contract W which includes the modeling and analysis of common naval radar scenarios using converted Multi-Role Missile Model (MRoMM) ballistic missile data, and the addition of bug fixes, execution speed improvements and usability improvements to the software. DRDC Ottawa has contracted C-CORE for software support services related to the implementation and analysis of Radar Resources Management (RRM) using the Adaptive Multi-Function Radar simulator (Adapt MFR). Analysis and testing was performed using the Adapt MFR version Simulation results were analyzed and contributed to collaborative research under NATO SET-223. DRDC Ottawa CR i

4 This page intentionally left blank. ii DRDC Ottawa CR

5 Table of contents Abstract i Table of contents iii List of figures List of tables vi x 1 Introduction Multi-Role Missile Model data conversion MRoMM plot data.plt format Adapt MFR trajectory input data format Coordinate systems used for conversion MRoMM Conversion operations (using MATLAB R ) Trajectory tested (B PLT) Naval simulations Naval simulation parameters Context scenario A Context scenario A Simulation results A1 results Context only Context with clutter Context and event Context and event with clutter A2 results Context only Context and clutter DRDC Ottawa CR iii

6 Context and event Context and event with clutter A2 with modified ballistic missile track update rates Context and event; 0.5 second interval Context and event with clutter; 0.5 second interval Context and event; 0.1 second interval Context and event with clutter; 0.1 second interval Context and event; 0.05 second interval Context and event with clutter; 0.05 second interval Azimuth clutter update GUI changes Data structure changes Simulator clutter modeling changes Usability improvements Surface clutter Azimuth hard-code Capability to use multiple target input files Default save of scenario parameters Antenna scanning limits Simulation run tagging Bug fixes Missile save Burst gain parameters Scheduler parameters Multiple jammer indexing Multiple pulse width indexing iv DRDC Ottawa CR

7 6.6 Function calling case issues Centroid issue at far range Default target parameters Divide by zero Empty ground type parameter Imaginary result for missile elevation Parameters for multiple radar faces Target structure mismatches Initial parameter check routine issues Analysis data file renaming Default communications setting Execution speed improvements Remove calculations from nested loops Avoid array copy operations Remove user interruptible breakpoint from main loop Use of short circuit logical operations Conclusions Recommendations Bibliography List of symbols/abbreviations/acronyms DRDC Ottawa CR v

8 List of figures Figure 1: Coordinate systems Figure 2: Coordinate conversion operations Figure 3: Ballistic missile launch region Figure 4: Conversion of MRoMM data set. (a) Original trajectories. (b) Bearing rotation. (c) north-east offset Figure 5: B PLT rotated and shifted: original (red) vs. converted (blue) Figure 6: Converted missile B PLT (plane view in Adapt MFR) Figure 7: Context A1 diagram Figure 8: Context A1 overview Figure 9: B PLT re-rotated and re-shifted: original (red) vs. converted (blue). 12 Figure 10: Missile tested with context A1 overview Figure 11: Context A2 diagram Figure 12: Context A2 ships Figure 13: Context A2 boats Figure 14: Context A2 planes Figure 15: Context A2 jets Figure 16: Context A2 birds Figure 17: Context A2 overview Figure 18: Context A1 only: (a) Track completeness. (b) Track occupancy. (c) Frame time. 21 Figure 19: Context A1 with clutter: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 20: Context A1 with event: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 21: Context A1 with event; number of targets by priority Figure 22: A1 event target ground truth vi DRDC Ottawa CR

9 Figure 23: A1 event target indication accuracy Figure 24: A1 event target RMSE Figure 25: Context A1 with event and clutter: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 26: A1 event target with clutter ground truth Figure 27: A1 event target with clutter indication accuracy Figure 28: A1 event with clutter target RMSE Figure 29: Context A2 only: (a) Track completeness. (b) Track occupancy. (c) Frame time. 29 Figure 30: Context A2 with clutter: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 31: Context A2 with event: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 32: Context A2 with event; number of targets by priority Figure 33: A2 event target ground truth Figure 34: A2 event target indication accuracy Figure 35: A2 event target RMSE Figure 36: Context A2 with event and clutter: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 37: A2 event target with clutter ground truth Figure 38: A2 event target with clutter indication accuracy Figure 39: A2 event with clutter target RMSE Figure 40: Context A2 with event; 0.5 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 41: A2 event target ground truth; 0.5 second interval Figure 42: A2 event target indication accuracy; 0.5 second interval Figure 43: A2 event target RMSE; 0.5 second interval DRDC Ottawa CR vii

10 Figure 44: Context A2 with event and clutter; 0.5 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 45: A2 event target with clutter ground truth; 0.5 second interval Figure 46: A2 event target with clutter indication accuracy; 0.5 second interval Figure 47: A2 event with clutter target RMSE; 0.5 second interval Figure 48: Context A2 with event; 0.1 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 49: A2 event target ground truth; 0.1 second interval Figure 50: A2 event target indication accuracy; 0.1 second interval Figure 51: A2 event target RMSE; 0.1 second interval Figure 52: Context A2 with event and clutter; 0.1 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 53: A2 event target with clutter ground truth; 0.1 second interval Figure 54: A2 event target with clutter indication accuracy; 0.1 second interval Figure 55: A2 event with clutter target RMSE; 0.1 second interval Figure 56: Context A2 with event; 0.05 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 57: A2 event target ground truth; 0.05 second interval Figure 58: A2 event target indication accuracy; 0.05 second interval Figure 59: A2 event target RMSE; 0.05 second interval Figure 60: Context A2 with event and clutter; 0.05 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time Figure 61: A2 event target with clutter ground truth; 0.05 second interval Figure 62: A2 event target with clutter indication accuracy; 0.05 second interval Figure 63: A2 event with clutter target RMSE; 0.05 second interval Figure 64: Adapt MFR environment - surface clutter GUI with new parameters Figure 65: Illustration of simulation environment with range and new azimuth parameters. 55 viii DRDC Ottawa CR

11 Figure 66: GUI and wait-bar association labels DRDC Ottawa CR ix

12 List of tables Table 1: MRoMM plot data.plt file content Table 2: Adapt MFR simulation parameters Table 3: Context A1 parameters: ships, boats and planes Table 4: Context A1 parameters: jets and birds Table 5: Context A2 parameters: ships Table 6: Context A2 parameters: boats Table 7: Context A2 parameters: recreational planes Table 8: Context A2 parameters: jets Table 9: Context A2 parameters: birds Table 10: Adapt MFR environment - surface clutter GUI with new parameters Table 11: environment-surfaceclutter-sea structure change Table 12: environment-surfaceclutter-land structure change Table 13: environment-anomalous pathloss-terraintype structure change x DRDC Ottawa CR

13 1 Introduction Defence Research & Development Canada (DRDC) Ottawa has contracted C-CORE for software support services related to the implementation and analysis of radar resource management (RRM) using the Adaptive Multi-Function radar simulator (Adapt MFR). All analysis and testing was performed using the Adapt MFR version The main purpose of this work was to model common naval radar scenarios using Adapt MFR simulations. At first using a base set of ten targets (context scenario A1) was used. The context was then expanded to model 100 targets (context scenario A2) which included additional commercial and recreational aircraft, ships, recreational boats and birds. Clutter and ballistic missiles were then added to the simulations. The simulations performed and the results are described in Section 3. The ballistic missile parameters were provided by a NATO partner and converted to a format compatible for use with Adapt MFR. This conversion process is described in Section 2. All of the simulations were run with a single independent radar. The simulation results were analyzed and used as contributions to collaborative research under NATO SET-223 and in support of the RRM work described in (Moo & Ding, 2015). During analysis and testing, the software was updated to repair any newly discovered (or previously known) bugs and to implement speed improvements in an effort to reduce simulation run time. Some usability improvements were also made. This work builds upon the previous work described in Brinson (2016). DRDC Ottawa CR 1

14 2 Multi-Role Missile Model data conversion Ballistic missile data in Multi-Role Missile Model (MRoMM) format was provided to DRDC by a UK NATO partner. It was converted to a format compatible with Adapt MFR. This section describes the conversion process. 2.1 MRoMM plot data.plt format Table 1 shows the format of the ballistic missile data provided. Only a few of these parameters were necessary to convert the trajectories to the format used by Adapt MFR which consists of 12 parameters. 2 DRDC Ottawa CR

15 Table 1: MRoMM plot data.plt file content 1 Simulation Time s 26 Angular velocity about deg/s the Body Frame x-axis 2 Vertical Component of deg 27 Angular velocity about deg/s Angle of Attack the Body Frame y-axis 3 Horizontal Component of deg 28 Angular velocity about deg/s Angle of Attack the Body Frame z-axis 4 Drag Coefficient 29 Body Pitch Attitude deg (Guidance Frame) (Theta) 5 Lift Coefficient 30 Body Yaw Attitude deg (Guidance Frame) (Psi) 6 Pitching Moment Coefficient 31 Body Roll Attitude deg (Guidance Frame) (Phi) 7 Pitch Damping Derivative 32 Predicted Cross Range m Miss Distance from T1 8 Axial Drag Coefficient 33 Predicted Down Range m Miss Distance from T1 9 Incidence (angle of attack) deg 34 Fuel Used kg 10 Mach Number mach 35 Missile Mass kg 11 Dynamic Pressure Pa 36 Axial (X) N Thrust Component 12 Centre of Pressure calibres 37 Lateral (Y) N Thrust Component 13 Demanded Pitch deg 38 Normal (Z) N Thrust Component 14 Demanded Yaw deg 39 Body Roll Moments N due to Thrust 15 Demanded Roll deg 40 Body Pitching N Moments due to Thrust 16 Cross Range Location m 41 Body Yawing Moments N w.r.t Target 1 (T1) due to Thrust 17 Down Range Location m 42 Magnitude of Thrust N w.r.t Target 1 (T1) 18 Flight Path Angle deg 43 Moments of Inertia kg m 2 (Gamma) about Body X Axes 19 Flight Path Heading deg 44 Moments of Inertia kg m 2 about Body Y Axes 20 Geodetic Altitude m 45 Moments of Inertia kg m 2 about Body Z Axes 21 Geodetic Latitude deg 46 Centre of Gravity Position m 22 Geodetic Longitude deg 47 Ground Range Covered m 23 Axial Acceleration m/s 2 48 Stage Number 24 Lateral Acceleration m/s 2 49 Section Number 25 Magnitude of Velocity m/s 50 Object ID Number DRDC Ottawa CR 3

16 2.2 Adapt MFR trajectory input data format The 12 parameters used to define each target in Adapt MFR are listed below: Time: Nx1 array; seconds Slant range: Nx1 array; meters Horizontal range: Nx1 array; meters Bearing (i.e. azimuth): Nx1 array; degrees Elevation: Nx1 array; degrees Speed (radial velocity): Nx1 array; meters/second Height: Nx1 array; meters Radar cross section (RCS): # Swerling: # Identification: string; hostile/friendly/unknown Confidence: # Platform ID: Nx1 array; # 2.3 Coordinate systems used for conversion The conversion of the MRoMM data required several coordinate system conversions using the coordinate systems listed below and shown in Figure 1. All conversion operations were performed in MATLAB R. The conversion process consisted of 14 operations. ECEF: earth-centered, earth-fixed X, Y, Z LLA: latitude (Ψ:psi), longitude (λ:lambda), altitude (from earth s center) ENU: east, north, up local spherical: azimuth (Φ:phi), elevation (Θ:theta), slant range 4 DRDC Ottawa CR

17 Figure 1: Coordinate systems 2.4 MRoMM Conversion operations (using MATLAB R ) The 14 operations used to convert the MRoMM data to Adapt MFR trajectory format are as follows (several functions from the MATLAB R Mapping Toolbox were used): 1. Read in trajectory Latitude, Longitude, Altitude and Time data from.plt files 2. Resample Latitude, Longitude and Altitude for fixed time intervals 3. Convert to local spherical Azimuth/Elevation/Slant Range coordinate system (geodetic2aer) 4. Rotate trajectory bearing angle (around the Up vector) 5. Convert to Geodetic LLA coordinates (aer2geodetic) 6. Convert to local ENU coordinates (geodetic2ned) 7. Offset trajectory in north and east directions Also offset in Up direction to prevent below ground trajectory (large north-east offsets) 8. Convert to Geodetic LLA coordinates (ned2geodetic) Save Height (altitude) 9. Convert to local spherical Azimuth/Elevation/Slant Range coordinate system (geodetic2aer) Save Bearing (azimuth) and Elevation 10. Convert to local ENU coordinates (geodetic2ned) 11. Calculate Horizontal Range (north-east distance from radar position) 12. Convert to ECEF (XYZ) coordinates (geodetic2ecef) 13. Calculate Slant Range (XYZ distance from radar position) 14. Calculate speed (radial velocity) using differences in Slant Range values Save converted trajectory file to.mat file (to be used by Adapt MFR) DRDC Ottawa CR 5

18 Figure 2 shows a graphical overview of the operations performed. The missiles (red arrow) are rotated in azimuth (orange arrow) and shifted in the east-north plane (blue arrow) into a 20x20 km launch region (green box) (Figure 3) centered West of the radar position. Figure 2: Coordinate conversion operations Figure 3: Ballistic missile launch region 6 DRDC Ottawa CR

19 Figure 4 shows the missile trajectories after each step in the conversion process (in the Adapt MFR plane view GUI window). (a) (b) (c) Figure 4: Conversion of MRoMM data set. (a) Original trajectories. (b) Bearing rotation. (c) north-east offset. 2.5 Trajectory tested (B PLT ) Figure 5 shows the missile trajectory that was used for initial testing simulations. The original missile profile (red) is compared to the converted profile (blue). The Adapt MFR plane view is shown in Figure 6. DRDC Ottawa CR 7

20 Figure 5: B PLT rotated and shifted: original (red) vs. converted (blue). Figure 6: Converted missile B PLT (plane view in Adapt MFR). 8 DRDC Ottawa CR

21 3 Naval simulations This section describes the naval radar simulations that were performed including the parameters used and results obtained and analyzed 3.1 Naval simulation parameters Several Adapt MFR simulations were performed first using a base set of ten targets (context scenario A1), then 100 targets (context scenario A2) which included commercial and recreational aircraft, ships, recreational boats and birds. Clutter and ballistic missiles were then combined with the context scenarios in the simulation. The ballistic missile parameters were provided by a NATO partner and converted into a format compatible with Adapt MFR. This was described previously in Section 2. The main simulation parameters used are listed in Table 2. All of the simulations described in this section were run with a single independent radar. Table 2: Adapt MFR simulation parameters Parameter Value Units Number of radars 1 Transmitter frequency 3e9 Hz Number of antenna bursts 1 Pulses per burst 8 Pulse compression ratio 512 Peak power 10 kw Track update interval: Target priority >= 0.75 (high) 1.5 s Track update interval: Target priority < s Pulse width (PW) 1.28E-5 s Pulse repetition frequency (PRF) 9303 Hz Max unambiguous range 16 km Max unambiguous velocity 465 m/s Antenna height 23 m Antenna boresight (north is 0 degrees) 0 degrees Azimuth detection scan limits w.r.t boresight (-90:90 physical scan) -60:60 degrees Azimuth beam spacing 1.5 degrees Elevation detection scan limits w.r.t boresight (-90:90 physical scan) -45:75 degrees Elevation beam spacing 1.5 degrees Antenna diameter (AZ and EL) 2.3 m Detection signal-to-noise ratio (SNR) threshold 5 db Detection Gain threshold (below max antenna gain) 20 db Bit Error Rate threshold 1 Max communications delay 0 s DRDC Ottawa CR 9

22 3.1.1 Context scenario A1 A top-down overview of the SET-223 naval scenario context A1 is shown in Figure 7. It consisted of six targets (two cargo ships, two recreational boats, two recreational planes), which were created using the Adapt MFR target generator. These six targets were saved in the file scenario task 8 context A1 6 tgts.mat. A commercial jet target was extracted from the scenario birds 3.mat data set. It was rotated in bearing by 80 degrees and shifted in time to 0 seconds. Any trajectory data past 600 seconds was removed. Another copy of this jet was made and rotated in bearing by 85 degrees. Finally, two bird targets were also extracted, rotated in bearing by 90 and 95 degrees and shifted in time. These four targets were saved in the file scenario birds 4.mat. Figure 7: Context A1 diagram Combined, Table 3 and Table 4 list the parameters of the ten targets in the context A1 target set. The clutter defined for the simulation consisted of: sea state 5 from 0 to 20 km; urban from 20 to 40 km; and mountains from 40 km outwards. Urban and mountain clutter was limited to -45:45 in azimuth from 0 degrees (north). Outside of these azimuth limits the clutter is defined as sea state 5. This was done in an attempt to generate the desired clutter context within the limits of the current clutter model capabilities. Also, note that the clutter reflectivity that is generated by the simulator is based on reference value tables hard-coded in the software. 10 DRDC Ottawa CR

23 Type Initial ground range (km) Initial Altitude (m) Table 3: Context A1 parameters: ships, boats and planes Initial forward Speed (m/s) Initial Heading (deg) Initial az (deg) Leg index Duration of thrust (s) Speed at end of leg (m/s) Altitude at end of leg (m) Heading diff; end of leg (deg) ship ship boat boat plane plane Type scenario birds 3 index Initial ground range (km) Table 4: Context A1 parameters: jets and birds Initial Altitude (m) Initial radial Speed (m/s) Initial Bearing (deg) Initial Elev (deg) Speed at end of leg (m/s) Altitude at end of leg (m) Bearing at end of leg (deg) Elev at end of leg (deg) jet jet bird bird RCS (m 2 ) RCS (m 2 ) Figure 8 shows an overview of the context A1 target set as displayed in Adapt MFR. Blue lines (surface targets) and red lines show target trajectories (where triangles denote start positions). The green and blue circle shows the radar location. Brown circles define clutter boundaries at specified ranges from the radar location. Figure 8: Context A1 overview The ballistic missile launch event (RBM ) used in the simulation was created by converting MRoMM ballistic missile trajectory file B PLT. The missile bearing was rotated 45 degrees and the missile location was shifted east by 20 km and north by 30 km to lie within a launch region of 50x50 km centered 15 km east and 30 km north of the radar location. The ballistic missile filename is scenario rbm4 tgt mat. Figure 9 compares the original (red) missile trajectory profile to the converted profile (blue). Figure 10 shows an overview of the ballistic missile tested with context A1. DRDC Ottawa CR 11

24 Figure 9: B PLT re-rotated and re-shifted: original (red) vs. converted (blue). Figure 10: Missile tested with context A1 overview 12 DRDC Ottawa CR

25 3.1.2 Context scenario A2 The A2 context consisted of 100 targets (shown in Figure 11). Eighty targets (20 cargo ships, 20 recreational boats, 20 recreational planes and 20 commercial jets) were created using the Adapt MFR target generator (data file A2 80 of 100 tgts.mat). Twenty bird targets were extracted from the scenario birds 3.mat data file, rotated in bearing and shifted in time (data file scenario just 20 birds.mat). All the birds were time shifted to 0 seconds and any additional trajectory data after 600 seconds was discarded. Figure 11: Context A2 diagram Table 5 (ships), Table 6 (boats), Table 7 (planes), Table 8 (jets) and Table 9 (birds) list the parameters of the context A2 target set. Red lines show target trajectories (squares denote start position, blue lines are surface targets). The green and blue circle shows the radar location. The brown circles define the clutter boundaries. The clutter used with context A1 was also used for these simulations. Figure 12 (ships), Figure 13 (boats), Figure 14 (planes), Figure 15 (jets), and Figure 16 (birds) show each of the target sets by type. The ballistic missile event (RBM ) was again used in this simulation (Figure 10, data file scenario rbm4 tgt mat). Figure 17 shows an overview of the context A2 target set as displayed in Adapt MFR. DRDC Ottawa CR 13

26 Firing time (s) Initial ground range (km) Initial Altitude (m) Initial forward Speed (m/s) Table 5: Context A2 parameters: ships Initial Heading (deg) Initial az (deg) Leg index Duration of thrust (s) Speed at end of leg (m/s) Altitude at end of leg (m) Heading diff; end of leg (deg) RCS (m 2 ) Figure 12: Context A2 ships 14 DRDC Ottawa CR

27 Firing time (s) Initial ground range (km) Initial Altitude (m) Initial forward Speed (m/s) Table 6: Context A2 parameters: boats Initial Heading (deg) Initial az (deg) Leg index Duration of thrust (s) Speed at end of leg (m/s) Altitude at end of leg (m) Heading diff; end of leg (deg) RCS (m 2 ) Figure 13: Context A2 boats DRDC Ottawa CR 15

28 Firing time (s) Initial ground range (km) Initial Altitude (m) Table 7: Context A2 parameters: recreational planes Initial forward Speed (m/s) Initial Heading (deg) Initial az (deg) Leg index Duration of thrust (s) Speed at end of leg (m/s) Altitude at end of leg (m) Heading diff; end of leg (deg) RCS (m 2 ) Figure 14: Context A2 planes 16 DRDC Ottawa CR

29 Firing time (s) Initial ground range (km) Initial Altitude (m) Initial forward Speed (m/s) Table 8: Context A2 parameters: jets Initial Heading (deg) Initial az (deg) Leg index Duration of thrust (s) Speed at end of leg (m/s) Altitude at end of leg (m) Heading diff; end of leg (deg) RCS (m 2 ) Figure 15: Context A2 jets DRDC Ottawa CR 17

30 scenario birds 2015 index Initial ground range (km) Initial Altitude (m) Table 9: Context A2 parameters: birds Initial radial Speed (m/s) Initial Bearing (deg) Initial Elev (deg) Speed at end of leg (m/s) Altitude at end of leg (m) Bearing at end of leg (deg) Elev at end of leg (deg) RCS (m 2 ) Figure 16: Context A2 birds 18 DRDC Ottawa CR

31 3.2 Simulation results Figure 17: Context A2 overview The results from the context A1 simulations will be discussed first followed by the context A2 results. The metrics used to measure tracker performance include: track occupancy - measure of the track time per frame; track completeness - ratio of total time a target is tracked to the time it is in the radar field of regard; surveillance frame time - the time between surveillance looks; shows the impact of tracking on the surveillance frame time; track indication accuracy (TIA) - measure of the error between the true target positions and the estimated track position; and root mean square error (RMSE) - measure of the difference between track estimates and true target trajectories. The implementation and testing of these metrics is described in detail in (Brinson & Chamberland, 2010) and (Brinson, 2010) and was based on The Technical Cooperation Program (TTCP) report (TR-SEN , 2008). For optimized tracking it is desirable to achieve a high track completeness while keeping a low track occupancy and surveillance frame time. Low TIA and RMSE should result in improved tracking and possibly higher track completeness. Note that the priority and resulting track update rate of the ballistic missile event tested is calculated like all other targets for the simulations performed. In the Adapt MFR tracker, prioritization of tracks is determined using a fuzzy logic implementation described in (Brinson & Chamberland, 2010). Track scheduling is determined using a time-balancing scheduler where track update rates are based on the fuzzy logic priority results. The implementation and testing of this functionality is described in detail in (Brinson, 2011). High priority targets were updated at 1.5 second intervals. All other targets were updated at 3 second intervals. However; the track update rates for the ballistic missile were specifically increased for the tests described in Section DRDC Ottawa CR 19

32 3.2.1 A1 results Four simulation types were performed using context A1: context only (ID = ); context with clutter (ID = ); context with event (ID = ); and context with event and clutter (ID = ) Context only Figure 18 shows the track completeness, track occupancy and frame time results for the context A1 scenario only (ID = ). Targets 1 and 2 are ships; targets 3 and 4 are boats; targets 5 and 6 are planes; targets 7 and 8 are jets; and targets 9 and 10 are birds. 20 DRDC Ottawa CR

33 (a) (b) (c) Figure 18: Context A1 only: (a) Track completeness. (b) Track occupancy. (c) Frame time Context with clutter Figure 19 shows the track completeness, track occupancy and frame time results for the context A1 scenario with clutter (ID = ). With the introduction of clutter the track completeness and track occupancy decreased. DRDC Ottawa CR 21

34 (a) (b) (c) Figure 19: Context A1 with clutter: (a) Track completeness. (b) Track occupancy. (c) Frame time Context and event Figure 20 shows the track completeness, track occupancy and frame time results for the context A1 scenario with a ballistic missile event (ID = ). The context target results are not changed by the inclusion of the ballistic missile. 22 DRDC Ottawa CR

35 (a) (b) (c) Figure 20: Context A1 with event: (a) Track completeness. (b) Track occupancy. (c) Frame time. Figure 21 shows the number of targets versus time based on priority determined by the tracker. High priory targets are in red and other targets are in blue. The total number of targets is shown in black. Figure 22 shows the true trajectory of the missile (green) in range, azimuth and elevation versus the radar detection region (red) and the resulting track (blue). The ballistic missile is not tracked once it passes over the radar and exceeds the azimuth and elevation scan region of the radar. DRDC Ottawa CR 23

36 Figure 21: Context A1 with event; number of targets by priority Figure 22: A1 event target ground truth Figure 23 shows the TIA in range, azimuth and elevation of the missile versus time and Figure 24 shows the RMSE versus time. The final RMSE for the ballistic missile was DRDC Ottawa CR

37 Figure 23: A1 event target indication accuracy Figure 24: A1 event target RMSE Context and event with clutter Figure 25 shows the track completeness, track occupancy and frame time results for the context A1 scenario with a ballistic missile event and clutter (ID = ). The track completeness and occupancy were reduced due to clutter. The track completeness of the ballistic missile dropped to 62% from the 84% result that had no clutter. Figure 26 shows the true trajectory of the missile (green) in range, azimuth and elevation versus the radar detection region (red) and the resulting track (blue). The track initiation for the missile is also delayed due to clutter. Figure 27 shows the track indication accuracy in range, azimuth and elevation versus time. Figure 28 shows the track RMSE versus time. The TIA results were worsened by clutter and the RMSE was also increased a little. The final RMSE for the ballistic missile increased to DRDC Ottawa CR 25

38 (a) (b) (c) Figure 25: Context A1 with event and clutter: (a) Track completeness. (b) Track occupancy. (c) Frame time. 26 DRDC Ottawa CR

39 Figure 26: A1 event target with clutter ground truth Figure 27: A1 event target with clutter indication accuracy Figure 28: A1 event with clutter target RMSE DRDC Ottawa CR 27

40 3.2.2 A2 results Four simulation types were performed using context A2: context only (ID = ); context with clutter (ID = ); context with event (ID = ); and context with event and clutter (ID = ). Again note that the priority and resulting track update rate of the ballistic missile is calculated like all other targets for the simulations described in this section (high priority second interval, all other targets - 3 second interval) Context only Figure 29 shows the track completeness, track occupancy and frame time results for the context A2 scenario only (ID = ). Targets 1 to 20 are ships; 21 to 40 are boats; 41 to 60 are planes; 61 to 80 are jets; and 81 to 100 are birds. 28 DRDC Ottawa CR

41 (a) (b) (c) Figure 29: Context A2 only: (a) Track completeness. (b) Track occupancy. (c) Frame time Context and clutter Figure 30 shows the track completeness, track occupancy and frame time results for the context A2 scenario with clutter (ID = ). The track occupancy and track occupancy results were reduced due to the introduction of clutter. The completeness of the bird targets was significantly reduced or eliminated due to clutter. DRDC Ottawa CR 29

42 (a) (b) (c) Figure 30: Context A2 with clutter: (a) Track completeness. (b) Track occupancy. (c) Frame time Context and event Figure 31 shows the track completeness, track occupancy and frame time results for the context A2 scenario with a ballistic missile event (ID = ). Figure 32 shows the number of targets versus time based on priority determined by the tracker. High priory targets are in red and other targets are in blue. The total number of targets is shown in black. 30 DRDC Ottawa CR

43 (a) (b) (c) Figure 31: Context A2 with event: (a) Track completeness. (b) Track occupancy. (c) Frame time. Figure 33 shows the true trajectory of the missile (green) in range, azimuth and elevation versus the radar detection region (red) and the resulting track (blue). The ballistic missile is not tracked once it passes over the radar and exceeds the azimuth and elevation scan region of the radar. Figure 34 shows the track indication accuracy of the missile in range, azimuth and elevation versus time. Figure 35 shows the missile track RMSE versus time. The final RMSE was DRDC Ottawa CR 31

44 Figure 32: Context A2 with event; number of targets by priority Figure 33: A2 event target ground truth Figure 34: A2 event target indication accuracy 32 DRDC Ottawa CR

45 Figure 35: A2 event target RMSE DRDC Ottawa CR 33

46 Context and event with clutter Figure 36 shows the track completeness, track occupancy and frame time results for the context A2 scenario with a ballistic missile event and clutter (ID = ). The track completeness of the ballistic missile (index 101) was reduced to 59% from 82% due to the inclusion of clutter. The completeness of the bird targets was again significantly reduced or eliminated due to clutter. (a) (b) (c) Figure 36: Context A2 with event and clutter: (a) Track completeness. (b) Track occupancy. (c) Frame time. 34 DRDC Ottawa CR

47 Figure 37 shows the true trajectory of the missile (green) in range, azimuth and elevation versus the radar detection region (red) and the resulting track (blue). The track commencement of the ballistic missile (index 101) was delayed due to the inclusion of clutter. Figure 38 shows the track indication accuracy in range, azimuth and elevation versus time. Figure 39 shows the track RMSE versus time. The TIA and RMSE results were similar to the results without clutter with the exception of a sharp increase in RMSE when the missile tracking began at around 55 seconds. The final RMSE for the ballistic missile increased to Figure 37: A2 event target with clutter ground truth Figure 38: A2 event target with clutter indication accuracy DRDC Ottawa CR 35

48 Figure 39: A2 event with clutter target RMSE A2 with modified ballistic missile track update rates For the following simulations, the track update rate for the ballistic missile event target specifically was increased. The track update interval was reduced to 0.5, 0.1 and 0.05 seconds. Other high priority targets were still updated at 1.5 seconds. All other targets were updated at 3 second intervals. The following six simulations were performed using context A2 with the adjusted track update rates: context with event, 0.5 second interval (ID = ); context with event and clutter, 0.5 second interval (ID = ); context with event, 0.1 second interval (ID = ); context with event and clutter, 0.1 second interval (ID = ); context with event, 0.05 second interval (ID = ); and context with event and clutter, 0.05 second interval (ID = ) Context and event; 0.5 second interval Figure 40 shows the track completeness, track occupancy and frame time results for the context A2 scenario with a ballistic missile event (ID = ). The track occupancy and frame times increased slightly during the time the ballistic missile was being tracked at the increased rate. The track completeness of the ballistic missile increased to 86% from 82% (at the regular rate). Figure 41 shows the true trajectory of the missile (green) in range, azimuth and elevation versus the radar detection region (red) and the resulting track (blue). Figure 42 shows the track indication accuracy in range, azimuth and elevation versus time. Figure 43 shows the track RMSE versus time. The TIA and RMSE results for the ballistic missile were reduced due to the increased rate, compared to the results at the regular track update rate but there was a noticeable rise near the end of the track. The final RMSE was reduced to DRDC Ottawa CR

49 (a) (b) (c) Figure 40: Context A2 with event; 0.5 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time. DRDC Ottawa CR 37

50 Figure 41: A2 event target ground truth; 0.5 second interval Figure 42: A2 event target indication accuracy; 0.5 second interval Figure 43: A2 event target RMSE; 0.5 second interval 38 DRDC Ottawa CR

51 Context and event with clutter; 0.5 second interval Figure 44 shows the track completeness, track occupancy and frame time results for the context A2 scenario with a ballistic missile event and clutter (ID = ). Again, the track occupancy and frame times increased during the time the ballistic missile was being tracked at the increased rate however track completeness and occupancy are reduced due to clutter. As before, the completeness of the bird targets was significantly reduced or eliminated due to clutter. Figure 45 shows the true trajectory of the missile (green) in range, azimuth and elevation versus the radar detection region (red) and the resulting track (blue). As with the 0.05 second update interval, the track commencement of the ballistic missile (index 101) was delayed due to the inclusion of clutter. Also the tracker experienced problems starting around 85 seconds and the track was lost earlier than in previous results. Figure 46 shows the track indication accuracy in range, azimuth and elevation versus time. Figure 47 shows the track RMSE versus time. The TIA results increased significantly after 85 seconds. The tracker was having trouble tracking the missile at this point and track was lost early. The track completeness dropped significantly to 40%. The final RMSE increased to due to the inclusion of clutter Context and event; 0.1 second interval Figure 48 shows the track completeness, track occupancy and frame time results for the context A2 scenario with a ballistic missile event (ID = ). The track occupancy and frame times increased during the time the ballistic missile was being tracked at the increased rate. The track completeness of the ballistic missile increased slightly to 84% with the increased rate from 82% with standard update rate. Figure 49 shows the true trajectory of the missile (green) in range, azimuth and elevation versus the radar detection region (red) and the resulting track (blue). Figure 50 shows the track indication accuracy in range, azimuth and elevation versus time. Figure 51 shows the track RMSE versus time. The TIA and RMSE results for the ballistic missile were significantly reduced due to the increased rate. The final RMSE was reduced to DRDC Ottawa CR 39

52 (a) (b) (c) Figure 44: Context A2 with event and clutter; 0.5 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time. 40 DRDC Ottawa CR

53 Figure 45: A2 event target with clutter ground truth; 0.5 second interval Figure 46: A2 event target with clutter indication accuracy; 0.5 second interval Figure 47: A2 event with clutter target RMSE; 0.5 second interval DRDC Ottawa CR 41

54 (a) (b) (c) Figure 48: Context A2 with event; 0.1 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time. 42 DRDC Ottawa CR

55 Figure 49: A2 event target ground truth; 0.1 second interval Figure 50: A2 event target indication accuracy; 0.1 second interval Figure 51: A2 event target RMSE; 0.1 second interval DRDC Ottawa CR 43

56 Context and event with clutter; 0.1 second interval Figure 52 shows the track completeness, track occupancy and frame time results for the context A2 scenario with a ballistic missile event and clutter (ID = ). Again, the track occupancy and frame times increased during the time the ballistic missile was being tracked at the increased rate however track completeness and occupancy are reduced due to clutter. The track completeness of the ballistic missile dropped to 64% from 84% without clutter but was still higher than the 59% result from the standard update rate. As before, the completeness of the bird targets was significantly reduced or eliminated due to clutter. Figure 53 shows the true trajectory of the missile (green) in range, azimuth and elevation versus the radar detection region (red) and the resulting track (blue). The track commencement of the ballistic missile (index 101) was delayed due to the inclusion of clutter. Figure 54 shows the track indication accuracy in range, azimuth and elevation versus time. Figure 55 shows the track RMSE versus time. The TIA and RMSE results were similar to the results without clutter with the exception of a sharp rise in RMSE when the missile tracking began at around 55 seconds. The final RMSE went up to due to the inclusion of clutter. 44 DRDC Ottawa CR

57 (a) (b) (c) Figure 52: Context A2 with event and clutter; 0.1 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time. DRDC Ottawa CR 45

58 Figure 53: A2 event target with clutter ground truth; 0.1 second interval Figure 54: A2 event target with clutter indication accuracy; 0.1 second interval Figure 55: A2 event with clutter target RMSE; 0.1 second interval 46 DRDC Ottawa CR

59 Context and event; 0.05 second interval Figure 56 shows the track completeness, track occupancy and frame time results for the context A2 scenario with a ballistic missile event (ID = ). The track occupancy and frame times increased during the time the ballistic missile was being tracked at the increased rate, more so than with the 0.1 second update interval. The track completeness of the ballistic missile increased more so to 86% from 84% with the 0.1 second interval and 82% with the regular rate. Figure 57 shows the true trajectory of the missile (green) in range, azimuth and elevation versus the radar detection region (red) and the resulting track (blue). Figure 58 shows the track indication accuracy in range, azimuth and elevation versus time. Figure 59 shows the track RMSE versus time. The TIA and RMSE results for the ballistic missile were again significantly reduced due to the increased rate, slightly more so than with the 0.1 second update interval. The final RMSE was further reduced to DRDC Ottawa CR 47

60 (a) (b) (c) Figure 56: Context A2 with event; 0.05 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time. 48 DRDC Ottawa CR

61 Figure 57: A2 event target ground truth; 0.05 second interval Figure 58: A2 event target indication accuracy; 0.05 second interval Figure 59: A2 event target RMSE; 0.05 second interval DRDC Ottawa CR 49

62 Context and event with clutter; 0.05 second interval Figure 60 shows the track completeness, track occupancy and frame time results for the context A2 scenario with a ballistic missile event and clutter (ID = ). Again, the track occupancy and frame times increased during the time the ballistic missile was being tracked at the increased rate however track completeness and occupancy are reduced due to clutter. As before, the completeness of the bird targets was significantly reduced or eliminated due to clutter. Figure 61 shows the true trajectory of the missile (green) in range, azimuth and elevation versus the radar detection region (red) and the resulting track (blue). The track commencement of the ballistic missile (index 101) was delayed due to the inclusion of clutter. As was the case when using the 0.5 second update interval, the tracker experienced problems starting around 85 seconds and the track was lost earlier than in previous results. Figure 62 shows the track indication accuracy in range, azimuth and elevation versus time. Figure 63 shows the track RMSE versus time. The TIA results increased significantly after 85 seconds. The tracker was having trouble tracking the missile at this point and track was lost early. The track completeness dropped significantly to 41%. The final RMSE again increased slightly to DRDC Ottawa CR

63 (a) (b) (c) Figure 60: Context A2 with event and clutter; 0.05 second interval: (a) Track completeness. (b) Track occupancy. (c) Frame time. DRDC Ottawa CR 51

64 Figure 61: A2 event target with clutter ground truth; 0.05 second interval Figure 62: A2 event target with clutter indication accuracy; 0.05 second interval Figure 63: A2 event with clutter target RMSE; 0.05 second interval 52 DRDC Ottawa CR

65 4 Azimuth clutter update This section describes the steps taken to extend the surface clutter model used by Adapt MFR. The previous release only allowed clutter types to be defined as ring shaped areas at specified ranges from the radar location, thus restricting the simulator to more homogeneous simulations. The work done during this task aimed to allow different clutter types to be used and varied in both the range and azimuth direction. To enable this update, the Adapt MFR GUI, data structure, and clutter simulation functions had to be adapted to enable definition of different clutter areas, and proper clutter modeling by the simulator. These changes have been divided into three categories: GUI changes - changes to the user interface; Data structure changes - changes to the internal Adapt MFR data structure; and Simulation clutter model changes - changes to the simulation portion to use the new structure. The following sections will describe each of these changes, as well as the relevant code sections within Adapt MFR that were changed during this upgrade. 4.1 GUI changes To enable entry and use of additional clutter sections in azimuth, both the number of azimuth sections and a method for editing each azimuth section within a range ring were required. This was accomplished by adding three parameters to the Environment - Surface Clutter selection in the Adapt MFR user interface. These parameters can be specified for each range ring, allowing the user to vary clutter type in both range and azimuth. The additional inputs can be seen in Figure 64 in green. These inputs are further described in Table 10. Table 10: Adapt MFR environment - surface clutter GUI with new parameters Field name number of azimuth select azimuth segment to edit azimuth where the terrain starts (degrees) Description breaks each range ring into the number of specified azimuth sections allows the user to edit a specific section allows the user to specify the azimuth angle bounds for the given section DRDC Ottawa CR 53

66 Figure 64: Adapt MFR environment - surface clutter GUI with new parameters Figure 65 illustrates how these new parameters work to set-up different clutter areas within the simulation environment. In the example given, four range rings are defined. Within each of these range rings, a different number of azimuth sections are defined as follows: Range ring 1 (0 - R1) has 3 azimuth sections (Az1 - Az2, Az2 - Az3, Az3 - Az1); Range ring 2 (R1 - R2) has 2 azimuth sections (Az1 - Az2, Az2 - Az1); Range ring 3 (R2 - R3) and 4 (R3 - ) have a single azimuth section. The following list shows the Adapt MFR code files that were changed:.\gui\cbsurfclutparams: - lines 140:165 - added to allow entry of number of azimuth terrain types per range region - lines 192:218 - added to allow for editing each azimuth terrain type - lines 243:267 - added to allow entry of the corresponding azimuth start value - line modified access to sstate variable, which can now be an array - line modified access to the landtype variable, which is now a cell structure - several other lines - GUI properties 54 DRDC Ottawa CR

67 Figure 65: Illustration of simulation environment with range and new azimuth parameters DRDC Ottawa CR 55

68 4.2 Data structure changes To enable the new data input to control azimuth clutter sections, changes to the Adapt MFR s environment structure were required. As the clutter functions are part of the Environment section in the GUI, the changes were made in the structure of the environment global variable. The two entries in the environment variable that required changes were as the following: environment-surfaceclutter-sea - this sub-structure contained sea-state and a clutter flag for each clutter section. environment-surfaceclutter-land - this sub-structure contained the land type and a clutter flag for each clutter section. environment-anomalous pathloss-terraintype - this sub-structure contained the range and ground type (no clutter, sea, land) for each clutter area. Table 11 shows the changes to the sub-structure environment-surfaceclutter-sea. These changes allow for the user to associate both sea clutter areas and different sea states to each of the azimuth sub-sections within a given range clutter ring. Table 11: environment-surfaceclutter-sea structure change Parameter Old version New version ClutterPresent sstate Flag for sea clutter in this range ring Sea State in this range ring Array of flags for sea clutter for each azimuth section in this range ring Array of sea states for each azimuth section in this range ring Table 12 shows the change to the sub-structure environment-surfaceclutter-land. These changes allow the user to associate both land clutter areas and different land cover types to each of the azimuth sections within a given range clutter ring. Table 12: environment-surfaceclutter-land structure change Parameter Old version New version ClutterPresent landtype Flag for land clutter in this range ring String land type in this range ring Array of flags for land clutter for each azimuth section in this range ring Cell Array of land types for each azimuth section in this range ring Table 13 shows the changes to the sub-structure environment-anomalous pathloss-terraintype. These changes allow the user to specify different azimuth clutter sections for each of the specified range rings. The following list shows the Adapt MFR code files that were changed to add these parameters to the interface: 56 DRDC Ottawa CR

69 Table 13: environment-anomalous pathloss-terraintype structure change Parameter Old version New version range groundtype azimuth Start range value for clutter ring Specify ground type for this range N/A no change Array of specified ground types for this range ring and the different azimuth values Array of azimuth start values for each clutter section within this range ring.\gui\cbdefaultparameters.m: - line added azimuth variable to environment structure - line make the default landtype a cell instead of an array in the environment structure.\gui\cbloadparams.m: - lines 366:374 - added check for azimuth field in environment structure.\gui\edituicontrol.m: - various lines to properly write to environment variable, to accommodate different azimuth clutter sections.\gui\saveenvparams.m: - lines 62:76 - changes and additions to properly save the user entered environment parameters to the environment global variable DRDC Ottawa CR 57

70 4.3 Simulator clutter modeling changes Due to time constraints, it was not possible to integrate the simulation functionality and validate during the project time line. As an incremental step in this direction, C-CORE was able to modify the simulation functionality enough to use the new environment global structure, while ignoring any azimuth clutter areas for the time being. This will allow the previously documented source code changes to be integrated into the current code but without the functionality changes. C-CORE can then quickly finish and integrate the functionality in the future. To integrate this new structure change into the simulation environment, the following source code files were changed in Adapt MFR:.\main\create report.m: - lines 303:315 - changed and added to allow report to include all range and azimuth parameters.\main\findlandandsea2.m (new file; modified version of findseaandland.m): - line 36 - modified access to groundtype variable - line 42 - modified access to sstate variable - line 55 - modified access to landtype variable - line 67 - modified access to sstate variable 58 DRDC Ottawa CR

71 5 Usability improvements Some new functionality was added to Adapt MFR to improve usability during simulation and debugging and to avoid simulation errors due to improper parameter settings. The modifications are described in the following sections. 5.1 Surface clutter Azimuth hard-code Description: To improve surface clutter modeling for the simulations performed in this report, in lieu of the upgrades described in Section 4, a change was made to the software to override the clutter type based on hard-coded azimuth angle limits. When the land clutter type is specified as urban or mountain and the azimuth angle exceeds plus-or-minus 45 degrees the clutter type is re-defined as sea clutter. Files affected:.\main\findseaandland2.m - new file (modified version of findseaandland.m).\main\surfmfr4mod opt.m - lines 249 & 286.\Main\add false alarms.m - line Capability to use multiple target input files Description: The capability to use multiple target input files was added. This was in-part done in support of the changes described in Section 2. At this time the additional target files are hard-coded in the software and must be changed in the file adapt mfr.m. Also, plotting parameters in the plane view GUI function were adjusted to display surface targets in blue (other targets are red) and to display the target number in black at the start of the trajectory (the target number is displayed in red or blue at the end of the trajectory). This helps the user to identify targets by type and locate the start and end points of each target trajectory. Files affected:.\main\adapt mfr.m - lines 16:32.\Main\adaptmfr run.m - lines 92:98 & 585:594.\Gui\cbpViewAzimuth.m - lines 40, 41 & 132:139.\Main\missile append - new file 5.3 Default save of scenario parameters Description: The requirement to save scenario parameters at the start of each simulation run by default was added to prevent the loss of parameters that may be required for future simulation analysis or debugging. Files affected:.\main\adaptmfr run.m - line 1025 DRDC Ottawa CR 59

72 5.4 Antenna scanning limits Description: The software was updated to use the azimuth and elevation scan limits defined in the Antenna Pattern Group of the Radar and Processing section of the GUI. These values were previously hard-coded. Files affected:.\gui\cbdefaultparameters.m - lines 315 & 316.\Main\whats next adaptive.m - lines 210, 211, 454, 460 & 461.\Main\whats next.m - lines 273, 279, 280, 286, 287, 303 & Simulation run tagging Description: The GUI title bar, the progress bar (wait-bar) and messages within the MATLAB R display are labeled with the time that Adapt MFR was started to associate the three together. An example is shown in Figure 66. This helps the user to differentiate the multiple items when running multiple scenarios simultaneously should the user wish to check status or stop a scenario without the risk of closing the wrong simulation windows. The current time displayed in the progress bar (wait-bar) is updated periodically with the current system time to verify that simulation has not stalled. Figure 66: GUI and wait-bar association labels Files affected:.\gui\adaptmfr.m - lines 16 & 44.\Gui\adaptmfr run.m - lines 57, 1038, 1081, 1089, 1108 & DRDC Ottawa CR

Networked Radar Capability for Adapt MFR Adapt MFR V Experiment results and software debug updates

Networked Radar Capability for Adapt MFR Adapt MFR V Experiment results and software debug updates Networked Radar Capability for Adapt MFR Adapt MFR V 3.2.8 Experiment results and software debug updates c Her Majesty the Queen in Right of Canada as represented by the Minister of National Defence, 2014

More information

Comparison of Two Detection Combination Algorithms for Phased Array Radars

Comparison of Two Detection Combination Algorithms for Phased Array Radars Comparison of Two Detection Combination Algorithms for Phased Array Radars Zhen Ding and Peter Moo Wide Area Surveillance Radar Group Radar Sensing and Exploitation Section Defence R&D Canada Ottawa, Canada

More information

Tracking of Moving Targets with MIMO Radar

Tracking of Moving Targets with MIMO Radar Tracking of Moving Targets with MIMO Radar Peter W. Moo, Zhen Ding Radar Sensing & Exploitation Section DRDC Ottawa Research Centre Presentation to 2017 NATO Military Sensing Symposium 31 May 2017 waveform

More information

Naval Surveillance Multi-beam Active Phased Array Radar (MAARS)

Naval Surveillance Multi-beam Active Phased Array Radar (MAARS) Naval Surveillance Multi-beam Active Phased Array Radar (MAARS) MAARS MAARS purpose: MAARS is multimode C-band acquisition radar for surveillance and weapon assignment. It perform automatic detection,

More information

INTRODUCTION. Basic operating principle Tracking radars Techniques of target detection Examples of monopulse radar systems

INTRODUCTION. Basic operating principle Tracking radars Techniques of target detection Examples of monopulse radar systems Tracking Radar H.P INTRODUCTION Basic operating principle Tracking radars Techniques of target detection Examples of monopulse radar systems 2 RADAR FUNCTIONS NORMAL RADAR FUNCTIONS 1. Range (from pulse

More information

RADAR CHAPTER 3 RADAR

RADAR CHAPTER 3 RADAR RADAR CHAPTER 3 RADAR RDF becomes Radar 1. As World War II approached, scientists and the military were keen to find a method of detecting aircraft outside the normal range of eyes and ears. They found

More information

ASM(AR) Demonstration Engagements Anti-Ship Missile Active Radar Homing

ASM(AR) Demonstration Engagements Anti-Ship Missile Active Radar Homing ASM(AR) Demonstration Engagements Anti-Ship Missile Active Radar Homing The demonstration scenarios are: 1) Demo_1: Anti-Ship missile versus target ship executing an evasive maneuver 2) Demo_2: Anti-Ship

More information

Rapid Prototyping a Two Channel Autopilot for a Generic Aircraft

Rapid Prototyping a Two Channel Autopilot for a Generic Aircraft Rapid Prototyping a Two Channel Autopilot for a Generic Aircraft YOGANANDA JEPPU Head R&D Systems Moog India Technology Center MATLAB EXPO India 2014 The Team Atit Mishra Basavaraj M Chethan CU Chinmayi

More information

A new Sensor for the detection of low-flying small targets and small boats in a cluttered environment

A new Sensor for the detection of low-flying small targets and small boats in a cluttered environment UNCLASSIFIED /UNLIMITED Mr. Joachim Flacke and Mr. Ryszard Bil EADS Defence & Security Defence Electronics Naval Radar Systems (OPES25) Woerthstr 85 89077 Ulm Germany joachim.flacke@eads.com / ryszard.bil@eads.com

More information

The Challenge: Increasing Accuracy and Decreasing Cost

The Challenge: Increasing Accuracy and Decreasing Cost Solving Mobile Radar Measurement Challenges By Dingqing Lu, Keysight Technologies, Inc. Modern radar systems are exceptionally complex, encompassing intricate constructions with advanced technology from

More information

Synthetic Aperture Radar (SAR) Analysis with STK

Synthetic Aperture Radar (SAR) Analysis with STK Synthetic Aperture Radar (SAR) Analysis with STK Problem Statement You are conducting an exercise testing a Spotlight Synthetic Aperture Radar (SAR) system over a ground site. An experimental satellite

More information

Radar Systems Engineering Lecture 15 Parameter Estimation And Tracking Part 1

Radar Systems Engineering Lecture 15 Parameter Estimation And Tracking Part 1 Radar Systems Engineering Lecture 15 Parameter Estimation And Tracking Part 1 Dr. Robert M. O Donnell Guest Lecturer Radar Systems Course 1 Block Diagram of Radar System Transmitter Propagation Medium

More information

59TH ANNUAL FUZE CONFERENCE MAY 3-5, 2016 CHARLESTON, SC Fuzing Challenges for Guided Ammunition

59TH ANNUAL FUZE CONFERENCE MAY 3-5, 2016 CHARLESTON, SC Fuzing Challenges for Guided Ammunition 59TH ANNUAL FUZE CONFERENCE MAY 3-5, 2016 CHARLESTON, SC Fuzing Challenges for Guided Ammunition Introduction: Finmeccanica Guided Ammunition DART (Driven Ammunition Reduced Time-of-flight) Fired by Naval

More information

Fundamental Concepts of Radar

Fundamental Concepts of Radar Fundamental Concepts of Radar Dr Clive Alabaster & Dr Evan Hughes White Horse Radar Limited Contents Basic concepts of radar Detection Performance Target parameters measurable by a radar Primary/secondary

More information

Coordinated radar resource management for networked phased array radars

Coordinated radar resource management for networked phased array radars DRDC-RDDC-2014-P96 Coordinated radar resource management for networked phased array radars Peter W. Moo and Zhen Ding Radar Sensing & Exploitation Section Defence Research and Development Canada Ottawa,

More information

ORCSM: Online Remote Controlling And Status Monitoring of DWR

ORCSM: Online Remote Controlling And Status Monitoring of DWR ORCSM: Online Remote Controlling And Status Monitoring of DWR Ashwini D N M.Tech(CSE) IV sem VTU-CPGS Bangalore, India Shalini S Kumar M.Tech(CSE) IV sem VTU-CPGS Bangalore, India Abstract ORCSM is the

More information

Antenna Measurement Software Features and Specifications

Antenna Measurement Software Features and Specifications Antenna Measurement Software Antenna emission measurement and characterization http://www.diamondeng.net 484 Main Street, Suite 16 Diamond Springs, CA 95619 (530) 626-3857 Software Features Test Equipment

More information

Worst-Case GPS Constellation for Testing Navigation at Geosynchronous Orbit for GOES-R

Worst-Case GPS Constellation for Testing Navigation at Geosynchronous Orbit for GOES-R Worst-Case GPS Constellation for Testing Navigation at Geosynchronous Orbit for GOES-R Kristin Larson, Dave Gaylor, and Stephen Winkler Emergent Space Technologies and Lockheed Martin Space Systems 36

More information

Module 2: Lecture 4 Flight Control System

Module 2: Lecture 4 Flight Control System 26 Guidance of Missiles/NPTEL/2012/D.Ghose Module 2: Lecture 4 Flight Control System eywords. Roll, Pitch, Yaw, Lateral Autopilot, Roll Autopilot, Gain Scheduling 3.2 Flight Control System The flight control

More information

GEOMETRIC RECTIFICATION OF EUROPEAN HISTORICAL ARCHIVES OF LANDSAT 1-3 MSS IMAGERY

GEOMETRIC RECTIFICATION OF EUROPEAN HISTORICAL ARCHIVES OF LANDSAT 1-3 MSS IMAGERY GEOMETRIC RECTIFICATION OF EUROPEAN HISTORICAL ARCHIVES OF LANDSAT -3 MSS IMAGERY Torbjörn Westin Satellus AB P.O.Box 427, SE-74 Solna, Sweden tw@ssc.se KEYWORDS: Landsat, MSS, rectification, orbital model

More information

STK Missile Defense. Introduction: Scenario Storyline:

STK Missile Defense. Introduction: Scenario Storyline: Introduction: STK Missile Defense STK provides missile defense professionals with an environment for performing system-level analysis of threats, sensors, communications, intercept engagements, and defense

More information

Introduction to Radar Systems. The Radar Equation. MIT Lincoln Laboratory _P_1Y.ppt ODonnell

Introduction to Radar Systems. The Radar Equation. MIT Lincoln Laboratory _P_1Y.ppt ODonnell Introduction to Radar Systems The Radar Equation 361564_P_1Y.ppt Disclaimer of Endorsement and Liability The video courseware and accompanying viewgraphs presented on this server were prepared as an account

More information

1 SINGLE TGT TRACKER (STT) TRACKS A SINGLE TGT AT FAST DATA RATE. DATA RATE 10 OBS/SEC. EMPLOYS A CLOSED LOOP SERVO SYSTEM TO KEEP THE ERROR SIGNAL

1 SINGLE TGT TRACKER (STT) TRACKS A SINGLE TGT AT FAST DATA RATE. DATA RATE 10 OBS/SEC. EMPLOYS A CLOSED LOOP SERVO SYSTEM TO KEEP THE ERROR SIGNAL TRACKING RADARS 1 SINGLE TGT TRACKER (STT) TRACKS A SINGLE TGT AT FAST DATA RATE. DATA RATE 10 OBS/SEC. EMPLOYS A CLOSED LOOP SERVO SYSTEM TO KEEP THE ERROR SIGNAL SMALL. APPLICATION TRACKING OF AIRCRAFT/

More information

Quantifying the Effects of Chaff Screening on Hardkill and Softkill Coordination

Quantifying the Effects of Chaff Screening on Hardkill and Softkill Coordination Screening on Hardkill and Softkill Coordination Nekmohamed Manji, Murat Kocakanat, and Agis Kitsikis Defence R&D Canada Ottawa Department of National Defence 3701 Carling Ave Ottawa, ON, K1A 0Z4 CANADA

More information

THE NASA/JPL AIRBORNE SYNTHETIC APERTURE RADAR SYSTEM. Yunling Lou, Yunjin Kim, and Jakob van Zyl

THE NASA/JPL AIRBORNE SYNTHETIC APERTURE RADAR SYSTEM. Yunling Lou, Yunjin Kim, and Jakob van Zyl THE NASA/JPL AIRBORNE SYNTHETIC APERTURE RADAR SYSTEM Yunling Lou, Yunjin Kim, and Jakob van Zyl Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive, MS 300-243 Pasadena,

More information

ELDES / METEK Weather Radar Systems. General Description

ELDES / METEK Weather Radar Systems. General Description General Description Our weather radars are designed for precipitation monitoring at both regional and urban scales. They can be advantageously used as gap fillers of existing radar networks particularly

More information

A Bistatic HF Radar for Current Mapping and Robust Ship Tracking

A Bistatic HF Radar for Current Mapping and Robust Ship Tracking A Bistatic HF Radar for Current Mapping and Robust Ship Tracking Dennis Trizna Imaging Science Research, Inc. V. 703-801-1417 dennis @ isr-sensing.com www.isr-sensing.com Objective: Develop methods for

More information

AIR ROUTE SURVEILLANCE 3D RADAR

AIR ROUTE SURVEILLANCE 3D RADAR AIR TRAFFIC MANAGEMENT AIR ROUTE SURVEILLANCE 3D RADAR Supplying ATM systems around the world for more than 30 years indracompany.com ARSR-10D3 AIR ROUTE SURVEILLANCE 3D RADAR ARSR 3D & MSSR Antenna Medium

More information

Bandwidth Requirements for Day-to-Day Operations on Canada s 700 MHz Public Safety Broadband Network

Bandwidth Requirements for Day-to-Day Operations on Canada s 700 MHz Public Safety Broadband Network 2017-05-02 DRDC-RDDC-2017-L130 Produced for: Mark Williamson, DG / DRDC Scientific Letter Bandwidth Requirements for Day-to-Day Operations on Canada s 700 MHz Public Safety Broadband Network Background

More information

A CYLINDRICAL NEAR-FIELD VS. SPHERICAL NEAR-FIELD ANTENNA TEST COMPARISON

A CYLINDRICAL NEAR-FIELD VS. SPHERICAL NEAR-FIELD ANTENNA TEST COMPARISON A CYLINDRICAL NEAR-FIELD VS. SPHERICAL NEAR-FIELD ANTENNA TEST COMPARISON Jeffrey Fordham VP, Sales and Marketing MI Technologies, 4500 River Green Parkway, Suite 200 Duluth, GA 30096 jfordham@mi-technologies.com

More information

How to configure processing on an HPx card to get the most information from the incoming radar video

How to configure processing on an HPx card to get the most information from the incoming radar video Successful Configuration of HPx Cards How to configure processing on an HPx card to get the most information from the incoming radar video Summary It is important to configure the processing on the HPx

More information

HAM RADIO DELUXE SATELLITES A BRIEF INTRODUCTION. Simon Brown, HB9DRV. Programmer- in- C hief

HAM RADIO DELUXE SATELLITES A BRIEF INTRODUCTION. Simon Brown, HB9DRV. Programmer- in- C hief HAM RADIO DELUXE SATELLITES A BRIEF INTRODUCTION Simon Brown, HB9DRV Programmer- in- C hief Last update: Sunday, November 30, 2003 User Guide The IC-703s used in this project were supplied by Martin Lynch

More information

DOppler RAdar Data Exchange Format DORADE

DOppler RAdar Data Exchange Format DORADE NCAR/TN-403+1 A NCAR TECHNCAL NOTE i~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ October 1994 m ~~m~l DOppler RAdar Data Exchange Format DORADE Wen-Chau Lee Craig Walther Richard Oye ATMOSPHERC TECHNOLOGY

More information

Weather Radar Systems. General Description

Weather Radar Systems. General Description General Description Our weather radars are designed for precipitation monitoring at both regional and urban scales. They can be advantageously used as gap filler of existing radar networks particularly

More information

RECOMMENDATION ITU-R S.1340 *,**

RECOMMENDATION ITU-R S.1340 *,** Rec. ITU-R S.1340 1 RECOMMENDATION ITU-R S.1340 *,** Sharing between feeder links the mobile-satellite service and the aeronautical radionavigation service in the Earth-to-space direction in the band 15.4-15.7

More information

Multi Sensor Data Fusion

Multi Sensor Data Fusion Multi Sensor Data Fusion for improved maritime traffic monitoring in the Canadian Arctic Giulia Battistello*, Martin Ulmke*, Javier Gonzalez*, Camilla Mohrdieck** (*) Fraunhofer FKIE Sensor Data and Information

More information

Adaptive SAR Results with the LiMIT Testbed

Adaptive SAR Results with the LiMIT Testbed Adaptive SAR Results with the LiMIT Testbed Gerald Benitz Adaptive Sensor Array Processing Workshop 7 June 2005 999999-1 Outline LiMIT collection platform SAR sidelobe recovery Electronic Protection (EP)

More information

ARCHIVED REPORT. For data and forecasts on current programs please visit or call

ARCHIVED REPORT. For data and forecasts on current programs please visit   or call Radar Forecast ARCHIVED REPORT For data and forecasts on current programs please visit www.forecastinternational.com or call +1 203.426.0800 Outlook Barring further developments, this report will be archived

More information

VHF Radar Target Detection in the Presence of Clutter *

VHF Radar Target Detection in the Presence of Clutter * BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 6, No 1 Sofia 2006 VHF Radar Target Detection in the Presence of Clutter * Boriana Vassileva Institute for Parallel Processing,

More information

MISB ST STANDARD. 27 February Metric Geopositioning Metadata Set. 1 Scope. 2 References. 2.1 Normative Reference

MISB ST STANDARD. 27 February Metric Geopositioning Metadata Set. 1 Scope. 2 References. 2.1 Normative Reference MISB ST 1107.1 STANDARD Metric Geopositioning Metadata Set 27 February 2014 1 Scope This Standard (ST) defines threshold and objective metadata elements for photogrammetric applications. This ST defines

More information

Potential interference from spaceborne active sensors into radionavigation-satellite service receivers in the MHz band

Potential interference from spaceborne active sensors into radionavigation-satellite service receivers in the MHz band Rec. ITU-R RS.1347 1 RECOMMENDATION ITU-R RS.1347* Rec. ITU-R RS.1347 FEASIBILITY OF SHARING BETWEEN RADIONAVIGATION-SATELLITE SERVICE RECEIVERS AND THE EARTH EXPLORATION-SATELLITE (ACTIVE) AND SPACE RESEARCH

More information

Lecture # 7 Coordinate systems and georeferencing

Lecture # 7 Coordinate systems and georeferencing Lecture # 7 Coordinate systems and georeferencing Coordinate Systems Coordinate reference on a plane Coordinate reference on a sphere Coordinate reference on a plane Coordinates are a convenient way of

More information

MISB RP 1107 RECOMMENDED PRACTICE. 24 October Metric Geopositioning Metadata Set. 1 Scope. 2 References. 2.1 Normative Reference

MISB RP 1107 RECOMMENDED PRACTICE. 24 October Metric Geopositioning Metadata Set. 1 Scope. 2 References. 2.1 Normative Reference MISB RP 1107 RECOMMENDED PRACTICE Metric Geopositioning Metadata Set 24 October 2013 1 Scope This Recommended Practice (RP) defines threshold and objective metadata elements for photogrammetric applications.

More information

Combining Air Defense and Missile Defense

Combining Air Defense and Missile Defense Brigadier General Armament Corp (ret.) Michel Billard Thalesraytheonsystems 1 Avenue Carnot 91883 MASSY CEDEX FRANCE michel.billard@thalesraytheon-fr.com ABSTRACT A number of NATO Nations will use fixed

More information

Synthetic Aperture Radar

Synthetic Aperture Radar Synthetic Aperture Radar Picture 1: Radar silhouette of a ship, produced with the ISAR-Processor of the Ocean Master A Synthetic Aperture Radar (SAR), or SAR, is a coherent mostly airborne or spaceborne

More information

Introduction to Radar Systems. Clutter Rejection. MTI and Pulse Doppler Processing. MIT Lincoln Laboratory. Radar Course_1.ppt ODonnell

Introduction to Radar Systems. Clutter Rejection. MTI and Pulse Doppler Processing. MIT Lincoln Laboratory. Radar Course_1.ppt ODonnell Introduction to Radar Systems Clutter Rejection MTI and Pulse Doppler Processing Radar Course_1.ppt ODonnell 10-26-01 Disclaimer of Endorsement and Liability The video courseware and accompanying viewgraphs

More information

Wave Sensing Radar and Wave Reconstruction

Wave Sensing Radar and Wave Reconstruction Applied Physical Sciences Corp. 475 Bridge Street, Suite 100, Groton, CT 06340 (860) 448-3253 www.aphysci.com Wave Sensing Radar and Wave Reconstruction Gordon Farquharson, John Mower, and Bill Plant (APL-UW)

More information

DETECTION OF SMALL AIRCRAFT WITH DOPPLER WEATHER RADAR

DETECTION OF SMALL AIRCRAFT WITH DOPPLER WEATHER RADAR DETECTION OF SMALL AIRCRAFT WITH DOPPLER WEATHER RADAR Svetlana Bachmann 1, 2, Victor DeBrunner 3, Dusan Zrnic 2 1 Cooperative Institute for Mesoscale Meteorological Studies, The University of Oklahoma

More information

Active Cancellation Algorithm for Radar Cross Section Reduction

Active Cancellation Algorithm for Radar Cross Section Reduction International Journal of Computational Engineering Research Vol, 3 Issue, 7 Active Cancellation Algorithm for Radar Cross Section Reduction Isam Abdelnabi Osman, Mustafa Osman Ali Abdelrasoul Jabar Alzebaidi

More information

Track Generation and Management Within ACES

Track Generation and Management Within ACES TRACK GENERATION AND MANAGEMENT WITHIN ACES Track Generation and Management Within ACES Chad W. Bates Rebecca J. Gassler Simon Moskowitz Michael J. Burke and Joshua M. Henly This article describes the

More information

Design of Accurate Navigation System by Integrating INS and GPS using Extended Kalman Filter

Design of Accurate Navigation System by Integrating INS and GPS using Extended Kalman Filter Design of Accurate Navigation System by Integrating INS and GPS using Extended Kalman Filter Santhosh Kumar S. A 1, 1 M.Tech student, Digital Electronics and Communication Systems, PES institute of technology,

More information

Passive Emitter Geolocation using Agent-based Data Fusion of AOA, TDOA and FDOA Measurements

Passive Emitter Geolocation using Agent-based Data Fusion of AOA, TDOA and FDOA Measurements Passive Emitter Geolocation using Agent-based Data Fusion of AOA, TDOA and FDOA Measurements Alex Mikhalev and Richard Ormondroyd Department of Aerospace Power and Sensors Cranfield University The Defence

More information

Exercise 4-1. Chaff Clouds EXERCISE OBJECTIVE

Exercise 4-1. Chaff Clouds EXERCISE OBJECTIVE Exercise 4-1 Chaff Clouds EXERCISE OBJECTIVE To demonstrate chaff as a method of denying target information to a radar. To verify whether MTI processing is an effective anti-chaff processing technique

More information

UAV: Design to Flight Report

UAV: Design to Flight Report UAV: Design to Flight Report Team Members Abhishek Verma, Bin Li, Monique Hladun, Topher Sikorra, and Julio Varesio. Introduction In the start of the course we were to design a situation for our UAV's

More information

ATM-ASDE System Cassiopeia-5

ATM-ASDE System Cassiopeia-5 Casseopeia-5 consists of the following componeents: Multi-Sensor Data Processor (MSDP) Controller Working Position (CWP) Maintenance Workstation The ASDE is able to accept the following input data: Sensor

More information

Brazil and Russia space cooperation: recent projects and future perspectives in the field of GNSS monitoring and SLR stations

Brazil and Russia space cooperation: recent projects and future perspectives in the field of GNSS monitoring and SLR stations Brazil and Russia space cooperation: recent projects and future perspectives in the field of GNSS monitoring and SLR stations Renato A. Borges (UnB) and Geovany A. Borges (UnB) Emails: raborges@ene.unb.br

More information

HAM RADIO DELUXE SATELLITES A BRIEF INTRODUCTION. Simon Brown, HB9DRV. Programmer- in- C hief

HAM RADIO DELUXE SATELLITES A BRIEF INTRODUCTION. Simon Brown, HB9DRV. Programmer- in- C hief HAM RADIO DELUXE SATELLITES A BRIEF INTRODUCTION Simon Brown, HB9DRV Programmer- in- C hief Last update: Sunday, September 26, 2004 User Guide The IC-703s and IC-7800s used in this project were supplied

More information

Sensor set stabilization system for miniature UAV

Sensor set stabilization system for miniature UAV Sensor set stabilization system for miniature UAV Wojciech Komorniczak 1, Tomasz Górski, Adam Kawalec, Jerzy Pietrasiński Military University of Technology, Institute of Radioelectronics, Warsaw, POLAND

More information

O T & E for ESM Systems and the use of simulation for system performance clarification

O T & E for ESM Systems and the use of simulation for system performance clarification O T & E for ESM Systems and the use of simulation for system performance clarification Dr. Sue Robertson EW Defence Limited United Kingdom e-mail: sue@ewdefence.co.uk Tuesday 11 March 2014 EW Defence Limited

More information

Direction Finding for Unmanned Aerial Systems Using Rhombic Antennas and Amplitude Comparison Monopulse. Ryan Kuiper

Direction Finding for Unmanned Aerial Systems Using Rhombic Antennas and Amplitude Comparison Monopulse. Ryan Kuiper Direction Finding for Unmanned Aerial Systems Using Rhombic Antennas and Amplitude Comparison Monopulse by Ryan Kuiper A thesis submitted to the Faculty of Graduate and Postdoctoral Affairs in partial

More information

Design and Development of Novel Two Axis Servo Control Mechanism

Design and Development of Novel Two Axis Servo Control Mechanism Design and Development of Novel Two Axis Servo Control Mechanism Shailaja Kurode, Chinmay Dharmadhikari, Mrinmay Atre, Aniruddha Katti, Shubham Shambharkar Abstract This paper presents design and development

More information

Set No.1. Code No: R

Set No.1. Code No: R Set No.1 IV B.Tech. I Semester Regular Examinations, November -2008 RADAR SYSTEMS ( Common to Electronics & Communication Engineering and Electronics & Telematics) Time: 3 hours Max Marks: 80 Answer any

More information

Space-Time Adaptive Processing Using Sparse Arrays

Space-Time Adaptive Processing Using Sparse Arrays Space-Time Adaptive Processing Using Sparse Arrays Michael Zatman 11 th Annual ASAP Workshop March 11 th -14 th 2003 This work was sponsored by the DARPA under Air Force Contract F19628-00-C-0002. Opinions,

More information

RDSI. Research and Development Solutions, Inc. EW Pro Technical Specification OVERVIEW. System Characteristics. Scenario Characteristics

RDSI. Research and Development Solutions, Inc. EW Pro Technical Specification OVERVIEW. System Characteristics. Scenario Characteristics RDSI Research and Development Solutions, Inc. EW Pro Technical Specification OVERVIEW System Characteristics Scenario Characteristics Platform Characteristics Emitter Characteristics Research and Development

More information

Final Examination. 22 April 2013, 9:30 12:00. Examiner: Prof. Sean V. Hum. All non-programmable electronic calculators are allowed.

Final Examination. 22 April 2013, 9:30 12:00. Examiner: Prof. Sean V. Hum. All non-programmable electronic calculators are allowed. UNIVERSITY OF TORONTO FACULTY OF APPLIED SCIENCE AND ENGINEERING The Edward S. Rogers Sr. Department of Electrical and Computer Engineering ECE 422H1S RADIO AND MICROWAVE WIRELESS SYSTEMS Final Examination

More information

39N6E KASTA-2E2 Low-Altitude 3D All-Round Surveillance Radar

39N6E KASTA-2E2 Low-Altitude 3D All-Round Surveillance Radar 39N6E KASTA-2E2 Low-Altitude 3D All-Round Surveillance Radar The Kasta-2E2 low-altitude 3D all-round surveillance radar is designed to control airspace and to perform automatic detection, range/azimuth/altitude

More information

The Delay-Doppler Altimeter

The Delay-Doppler Altimeter Briefing for the Coastal Altimetry Workshop The Delay-Doppler Altimeter R. K. Raney Johns Hopkins University Applied Physics Laboratory 05-07 February 2008 1 What is a Delay-Doppler altimeter? Precision

More information

ATS 351 Lecture 9 Radar

ATS 351 Lecture 9 Radar ATS 351 Lecture 9 Radar Radio Waves Electromagnetic Waves Consist of an electric field and a magnetic field Polarization: describes the orientation of the electric field. 1 Remote Sensing Passive vs Active

More information

PHOTOGRAMMETRIC RESECTION DIFFERENCES BASED ON LABORATORY vs. OPERATIONAL CALIBRATIONS

PHOTOGRAMMETRIC RESECTION DIFFERENCES BASED ON LABORATORY vs. OPERATIONAL CALIBRATIONS PHOTOGRAMMETRIC RESECTION DIFFERENCES BASED ON LABORATORY vs. OPERATIONAL CALIBRATIONS Dean C. MERCHANT Topo Photo Inc. Columbus, Ohio USA merchant.2@osu.edu KEY WORDS: Photogrammetry, Calibration, GPS,

More information

RECOMMENDATION ITU-R SA.1628

RECOMMENDATION ITU-R SA.1628 Rec. ITU-R SA.628 RECOMMENDATION ITU-R SA.628 Feasibility of sharing in the band 35.5-36 GHZ between the Earth exploration-satellite service (active) and space research service (active), and other services

More information

NCUBE: The first Norwegian Student Satellite. Presenters on the AAIA/USU SmallSat: Åge-Raymond Riise Eystein Sæther

NCUBE: The first Norwegian Student Satellite. Presenters on the AAIA/USU SmallSat: Åge-Raymond Riise Eystein Sæther NCUBE: The first Norwegian Student Satellite Presenters on the AAIA/USU SmallSat: Åge-Raymond Riise Eystein Sæther Motivation Build space related competence within: mechanical engineering, electronics,

More information

Vaisala Radiotheodolite RT20

Vaisala Radiotheodolite RT20 Vaisala Radiotheodolite RT20 The artilleryman's choice for passive and independent upper-air windfinding Passive and Independent Windfinding at its Best The Vaisala RT20 Radiotheodolite is the workhorse,

More information

Design of an Airborne SLAR Antenna at X-Band

Design of an Airborne SLAR Antenna at X-Band Design of an Airborne SLAR Antenna at X-Band Markus Limbach German Aerospace Center (DLR) Microwaves and Radar Institute Oberpfaffenhofen WFMN 2007, Markus Limbach, Folie 1 Overview Applications of SLAR

More information

AN/APN-242 Color Weather & Navigation Radar

AN/APN-242 Color Weather & Navigation Radar AN/APN-242 Color Weather & Navigation Radar Form, Fit and Function Replacement for the APN-59 Radar Previous Configuration: APN-59 Antenna Stabilization Data Generator Antenna Subsystem Radar Receiver

More information

Corresponding author address: Valery Melnikov, 1313 Haley Circle, Norman, OK,

Corresponding author address: Valery Melnikov, 1313 Haley Circle, Norman, OK, 2.7 EVALUATION OF POLARIMETRIC CAPABILITY ON THE RESEARCH WSR-88D Valery M. Melnikov *, Dusan S. Zrnic **, John K. Carter **, Alexander V. Ryzhkov *, Richard J. Doviak ** * - Cooperative Institute for

More information

ERS-2 SAR CYCLIC REPORT

ERS-2 SAR CYCLIC REPORT 28TH SEPTEMBER 2009-2ND NOVEMBER 2009 (CYCLE 151) PUBLIC SUMMARY prepared by/préparé par IDEAS SAR Team reference/réference IDEAS-BAE-OQC-REP-0245 issue/édition 9 revision/révision 0 date of issue/date

More information

Radar Equations. for Modern Radar. David K. Barton ARTECH HOUSE BOSTON LONDON. artechhouse.com

Radar Equations. for Modern Radar. David K. Barton ARTECH HOUSE BOSTON LONDON. artechhouse.com Radar Equations for Modern Radar David K Barton ARTECH HOUSE BOSTON LONDON artechhousecom Contents Preface xv Chapter 1 Development of the Radar Equation 1 11 Radar Equation Fundamentals 1 111 Maximum

More information

Kalman Tracking and Bayesian Detection for Radar RFI Blanking

Kalman Tracking and Bayesian Detection for Radar RFI Blanking Kalman Tracking and Bayesian Detection for Radar RFI Blanking Weizhen Dong, Brian D. Jeffs Department of Electrical and Computer Engineering Brigham Young University J. Richard Fisher National Radio Astronomy

More information

Simulating Automatic Obscuration and Multipath for Realistic GNSS Receiver Testing Application Note

Simulating Automatic Obscuration and Multipath for Realistic GNSS Receiver Testing Application Note Simulating Automatic Obscuration and Multipath for Realistic GNSS Testing Application Note Products: R&S SMBV100A The R&S SMBV100A is both, a versatile general-purpose vector signal generator and a powerful

More information

AircraftScatterSharp New Features

AircraftScatterSharp New Features Aircraft Scatter Is using aircraft to redirect or scatter RF that would otherwise be lost in space Increases Communications Distance Has increasing advantage over troposcatter as frequency increases Has

More information

Scalable Front-End Digital Signal Processing for a Phased Array Radar Demonstrator. International Radar Symposium 2012 Warsaw, 24 May 2012

Scalable Front-End Digital Signal Processing for a Phased Array Radar Demonstrator. International Radar Symposium 2012 Warsaw, 24 May 2012 Scalable Front-End Digital Signal Processing for a Phased Array Radar Demonstrator F. Winterstein, G. Sessler, M. Montagna, M. Mendijur, G. Dauron, PM. Besso International Radar Symposium 2012 Warsaw,

More information

Introduction to Radar Systems. Radar Antennas. MIT Lincoln Laboratory. Radar Antennas - 1 PRH 6/18/02

Introduction to Radar Systems. Radar Antennas. MIT Lincoln Laboratory. Radar Antennas - 1 PRH 6/18/02 Introduction to Radar Systems Radar Antennas Radar Antennas - 1 Disclaimer of Endorsement and Liability The video courseware and accompanying viewgraphs presented on this server were prepared as an account

More information

Space Frequency Coordination Group

Space Frequency Coordination Group Space Frequency Coordination Group Report SFCG 38-1 POTENTIAL RFI TO EESS (ACTIVE) CLOUD PROFILE RADARS IN 94.0-94.1 GHZ FREQUENCY BAND FROM OTHER SERVICES Abstract This new SFCG report analyzes potential

More information

Detection of Targets in Noise and Pulse Compression Techniques

Detection of Targets in Noise and Pulse Compression Techniques Introduction to Radar Systems Detection of Targets in Noise and Pulse Compression Techniques Radar Course_1.ppt ODonnell 6-18-2 Disclaimer of Endorsement and Liability The video courseware and accompanying

More information

Acoustic Based Angle-Of-Arrival Estimation in the Presence of Interference

Acoustic Based Angle-Of-Arrival Estimation in the Presence of Interference Acoustic Based Angle-Of-Arrival Estimation in the Presence of Interference Abstract Before radar systems gained widespread use, passive sound-detection based systems were employed in Great Britain to detect

More information

CHAPTER 1 INTRODUCTION

CHAPTER 1 INTRODUCTION 1 CHAPTER 1 INTRODUCTION In maritime surveillance, radar echoes which clutter the radar and challenge small target detection. Clutter is unwanted echoes that can make target detection of wanted targets

More information

DOPPLER RADAR. Doppler Velocities - The Doppler shift. if φ 0 = 0, then φ = 4π. where

DOPPLER RADAR. Doppler Velocities - The Doppler shift. if φ 0 = 0, then φ = 4π. where Q: How does the radar get velocity information on the particles? DOPPLER RADAR Doppler Velocities - The Doppler shift Simple Example: Measures a Doppler shift - change in frequency of radiation due to

More information

SODAR- sonic detecting and ranging

SODAR- sonic detecting and ranging Active Remote Sensing of the PBL Immersed vs. remote sensors Active vs. passive sensors RADAR- radio detection and ranging WSR-88D TDWR wind profiler SODAR- sonic detecting and ranging minisodar RASS RADAR

More information

BURIED OBJECT SCANNING SONAR (BOSS)

BURIED OBJECT SCANNING SONAR (BOSS) BURIED OBJECT SCANNING SONAR (BOSS) The BOSS-SAS (Buried Object Scanning Sonar-Synthetic Aperture Sonar) system is a bottom looking sonar used for the detection and imaging of bottom and buried targets.

More information

WE-525T Antenna Analyzer Manual and Specification

WE-525T Antenna Analyzer Manual and Specification WE-525T Antenna Analyzer Manual and Specification 1.0 Description This product is designed to speed and ease the testing and tuning of antenna systems. Graphical displays of SWR, Return loss, Distance

More information

Characteristics of HF Coastal Radars

Characteristics of HF Coastal Radars Function Characteristics System 1 Maximum operational (measurement) range** Characteristics of HF Coastal Radars 5 MHz Long-range oceanographic 160-220 km average during (daytime)* System 2 System 3 System

More information

SAMPLE QUESTION PAPER III ENGINEERING GRAPHICS (046) Time Allowed: 3 hours Maximum Marks: 70

SAMPLE QUESTION PAPER III ENGINEERING GRAPHICS (046) Time Allowed: 3 hours Maximum Marks: 70 SAMPLE QUESTION PAPER III ENGINEERING GRAPHICS (046) Time Allowed: 3 hours Maximum Marks: 70 Note: (i) Attempt all the questions. (ii) Use both sides of the drawing sheet, if necessary. (iii) All dimensions

More information

APPENDIX B - MOUNT SPECIFIC DATA For SweDish Radar Finder

APPENDIX B - MOUNT SPECIFIC DATA For SweDish Radar Finder RC3000 Antenna Controller Appendix F RC3000 Data Sheet 1 APPENDIX B - MOUNT SPECIFIC DATA For SweDish Radar Finder This appendix describes RC3000 operations unique for the SweDish Radar Finder mount. Differences

More information

Implementation of a VHF Spherical Near-Field Measurement Facility at CNES

Implementation of a VHF Spherical Near-Field Measurement Facility at CNES Implementation of a VHF Spherical Near-Field Measurement Facility at CNES Gwenn Le Fur, Guillaume Robin, Nicolas Adnet, Luc Duchesne R&D Department MVG Industries Villebon-sur-Yvette, France Gwenn.le-fur@satimo.fr

More information

MISB ST STANDARD

MISB ST STANDARD MISB ST 0902.3 STANDARD Motion Imagery Sensor Minimum Metadata Set 27 February 2014 1 Scope This Standard defines the Motion Imagery Sensor Minimum Metadata Set (MISMMS) that enables the basic capabilities

More information

The Old Cat and Mouse Game Continues

The Old Cat and Mouse Game Continues The Old Cat and Mouse Game Continues or, How Advances in Radar Development Drive Testing Requirements for Next Generation EW Systems by: Walt Schulte Agilent Technologies Microwave and Communications Division

More information

Microwave Remote Sensing (1)

Microwave Remote Sensing (1) Microwave Remote Sensing (1) Microwave sensing encompasses both active and passive forms of remote sensing. The microwave portion of the spectrum covers the range from approximately 1cm to 1m in wavelength.

More information

Information on the Evaluation of VHF and UHF Terrestrial Cross-Border Frequency Coordination Requests

Information on the Evaluation of VHF and UHF Terrestrial Cross-Border Frequency Coordination Requests Issue 1 May 2013 Spectrum Management and Telecommunications Technical Bulletin Information on the Evaluation of VHF and UHF Terrestrial Cross-Border Frequency Coordination Requests Aussi disponible en

More information

SeaSonde Radial Site Release 6 CrossLoopPatterner Application Guide Apr 21, 2009 Copyright CODAR Ocean Sensors, Ltd

SeaSonde Radial Site Release 6 CrossLoopPatterner Application Guide Apr 21, 2009 Copyright CODAR Ocean Sensors, Ltd CODAR O C E A N S E N S O R S SeaSonde Radial Site Release 6 CrossLoopPatterner Application Guide Apr 21, 2009 Copyright CODAR Ocean Sensors, Ltd CrossLoopPatterner is an utility for converting LOOP files

More information

FieldGenius Technical Notes GPS Terminology

FieldGenius Technical Notes GPS Terminology FieldGenius Technical Notes GPS Terminology Almanac A set of Keplerian orbital parameters which allow the satellite positions to be predicted into the future. Ambiguity An integer value of the number of

More information