High Latitude Ionospheric Scintillation Studies Using Multi-Constellation Multi-Band GNSS Receivers

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1 High Latitude Ionospheric Scintillation Studies Using Multi-Constellation Multi-Band GNSS Receivers Jade Morton Department of Electrical and Computer Engineering Colorado State University Slide 1

2 Society s Increasing Dependence on GPS Slide 2

3 Satellite Navigation Modernization GPS GLONASS Galileo Beidou IRNSS QZSS 1 Civil Signal 6 Civil Signals, 3 frequency bands 21 st Century: > $50B Investment SBAS Today: 25~35 Satellites In View 2023: >160 Navigation Satellites > 400 Signals in Space Navigation: 4 Satellites A Huge Winner: Remote Sensing with GNSS Slide 3

4 AFOSR Project Objectives 1. Utilize the GNSS scintillation observations to infer ionosphere irregularity morphology and climatology 2. Establish the relationship btw ionosphere scintillation and geomagnetic field disturbances 3. Evaluate the impact of high latitude scintillation on radio wave propagation 4. Investigate physical mechanisms responsible for the creation and evolution of high latitude ionosphere irregularities Slide 4

5 Ionosphere Delay and Scintillation Satellite velocity Ionosphere TEC 1. Range error: dr µ TEC f 2 Plasma turbulence 2. Scintillation: Amplitude fading Random phase variation Slide 5

6 # 10 7 High Latitude Scintillation Example 2 Power ? (cycles) Time (UTC) Slide 6

GNSS Receiver Processing Affects Ionosphere Measurements An ionosphere structure is indicated in amplitude measurement L1CA L2C Pseudorange L1CA

7 GNSS Receiver Processing Affects Ionosphere Measurements An ionosphere structure is indicated in amplitude measurement L1CA L2C Pseudorange L1CA L2P Pseudorange L1CA L2C Carrier-smoothed Pseudorange L1CA L2P Carrier-smoothed Pseudorange Time (UTC) Challenge 1: Measurement Accuracy Slide 7

8 GNSS Receivers Loss Lock of Signals Front end hardware Signal conditioning Sampling MHz Raw data Signal processing: amplitude frequency phase 100Hz Measurements Nav. processing: SV orbit decode data correct error 10Hz Nav solution P V T Large disturbances Low energy Wrong parameter estimations From Sampling device Correlators Estimators Reference Generation Filters Signal parameters Challenge 2: Measurement Availability Slide 8

E-DAS: Event-driven Data Acquisition System Space Weather Events Internet VPN Data Center at Home Institution GNSS Algorithm Development Low rate C-DAS Commercial ISM Receiver Data Collection and

9 E-DAS: Event-driven Data Acquisition System Space Weather Events Internet VPN Data Center at Home Institution GNSS Algorithm Development Low rate C-DAS Commercial ISM Receiver Data Collection and Control Server Space Weather Event Monitoring & Trigger Software Advanced Receiver Signal Processing Algorithm Library RF Front End 1 All Sat Nav Open RF Front Signals End 2 Remote Reconfigurable Circular Buffer Circular Buffer Data Storage Ionosphere Space Weather Studies RF Front End N Circular Buffer Slide 9

10 CSU GNSS Network ~350TB and growing Morton, Y., Y. Jiao, and S. Taylor, High-latitude and equatorial ionospheric scintillation based on an event-driven multi-gnss data collection system, Proc. Ionospheric Effects Sym., Alexandria, Slide 10 VA, May 2015.

11 GNSS For Ionosphere Monitoring/Studying How to create event trigger? How do we process the data? What are our findings? 1. Ionosphere irregularity morphology/climatology based on GNSS observations 2. Relationship btw ionosphere scintillation and geomagnetic field disturbances 3. Impact of high latitude scintillation on radio wave propagation 4. Physical mechanisms responsible for the creation and evolution of high latitude ionosphere plasma irregularities Slide 11

12 Findings Related to Objective 1, 2 1. Ionosphere irregularity morphology/climatology based on GNSS observations 2. Relationship between ionosphere scintillation and geomagnetic field disturbances Jiao, Y. and Y. Morton, Comparison of the effects of high-latitude and equatorial ionospheric scintillation on GPS signals during the maximum of solar cycle 24, Radio Sci., 50(9), , /2015RS005719, Jiao, Y., Y. Morton, S. Taylor, W. Pelgrum, Scintillating statistics, GPS World, Oct Jiao, Y., Y. Morton, S. Taylor, W. Pelgrum, Characterization of high latitude ionospheric scintillation of GPS signals, Radio Sci., 48, doi: /2013rs005259, Slide 12

13 High Latitude Scintillation Spatial Distribution HAARP GPS Only Magnetic zenith Slide 13

14 Probability Diurnal Patterns Ascension Island Jicamarca, Peru Singapore Equatorial 0.3 Gakona, Alaska Hours after sunset Slide 14

15 Solar Cycle Dependence: High & Low Latitude Slide 15

16 +1000 Correlation Btw Geomagnetic Field Disturbance and GNSS Measurement Error 2015/12/20 Poker Flat, Alaska Poker Flat, AK, 12/20/ Poker Bh (nt) Bh Bz Poker Bz (nt) 100 <? (degrees) GPS GLONASS Galileo Time (UT hours) Slide 16

17 Statistical Correlation: Magnetic Field Disturbance & GNSS Errors Probability of maxs f >30 o maxh - minh maxd - mind maxz - minz (H 2 +D 2 +Z 2 ) 1/2 peak-to-peak (nt) Slide 17

18 Findings Related to Objective 3 3. Impact of high latitude scintillation on radio wave propagation Lee, J., Y. Morton, J. Lee, H-S. Moon, J. Seo, Monitoring and mitigation of ionospheric anomalies for GNSS-based safety critical systems, accepted, Special issue on Advances in Signal Processing for Global Navigation Satellite Systems, IEEE Signal Processing Magazine, Myer, G., Y. Morton, B. Schipper, Ionospheric scintillation effects on GPS pseudorange and carrier phase measurements and an adaptive algorithm to limit position errors during scintillation, Proc. ION ITM, Monterey, CA, Jan Jiao, Y., D. Xu, C. Rino, Y. Morton, Simulation and characterization of multi-frequency strong equatorial ionospheric scintillation, submitted to IEEE Trans. Aero. Elec. Sys., 2017 Rino, C., C. Currano, K. Groves, and J. Morton, The ramifications of configuration-space models for GNSS scintillation, URSI National Meeting, Jan Rino, C., C. Carrano, Y. Morton, Y. Jiao, J. Wang, and D. Xu, On the geometric dependence of scintillation and stochastic structure models, Proc. Beacon Satellite Sym., June Slide 18

19 Multi-GNSS Scintillation Signal Simulator Physics-Based, Data-Consistent, Multi-Platform Slide 19

20 Findings Related to Objective 4 4. Physical mechanisms responsible for the creation and evolution of high latitude ionosphere plasma irregularities Wang, J., Y. Morton, A comparative study of ionospheric irregularity drift velocity derived from a GNSS receiver array and PFISR measurements during high latitude ionospheric scintillation, under review, J. Geophy. Res., R. Robinson, J. Wang, J. Morton, J. Shim, J. Secan, Comparative study of GNSS phase scintillation and high latitude electrodynamic ionospheric properties derived from AMPERE, submitted to Ionosphere Effects Sym., Rino, C., C. Currano, K. Groves, and J. Morton, The ramifications of configurationspace models for GNSS scintillation, URSI National Meeting, Jan Wang, J., Y. Morton, J. Spaleta, W. Bristow, A comparative study of ionospheric irregularity drift velocity using a GNSS receiver array and SuperDARN at high latitude, Proc. ION ITM, Monterey, CA, Jan Wang, J., Y. Morton, High latitude ionospheric irregularity drift velocity estimation using spaced GPS receiver carrier phase time-frequency analysis, IEEE Trans. Geosci. Remote Sensing, 53(11), , doi: /tgrs , Slide 20

21 Ionosphere Structure Drift Observation with GNSS Array Slide 21

22 Multi-GNSS Array at Poker Flat, AK Poker Flat Incoherent Scatter Radar Ant 3 Multi-Constellation GNSS Receiver Array Ant 1 Ant 2 Slide 22

23 Slide 23

24 Validation: GNSS Array vs. Incoherent Scatter Radar Slide 24

25 Irregularity Drift Velocity: GNSS vs. PFISR GNSS 12/20/2015, Poker Flat PFISR Slide 25

26 Mean Drift Velocity Comparison: GNSS vs PFISR 12/20/2015 Poker Flat Wang, J., Y. Morton, A comparative study of ionospheric irregularity drift velocity derived from a GNSS receiver array and PFISR measurements during high latitude ionospheric scintillation, submitted to J. Geophy. Res., Slide 26

27 Comparison: GNSS Phase Error vs. AMPERE E Field North 12/20/2015 Poker Flat Slide 27

28 Slide 28

29 Relevant Collaboration with Other Researchers Mahmoudian, R., W. Scales, P. Bernhardt, Y. Morton, S. Taylor, K. Papadopoulos, Y. Yampolski, G. Milikh, S. Ghader, and A. Najmi, Artificial ionospheric GPS phase scintillation excited during radiowave heating of the ionosphere, submitted to Ann. Geophys., Najmi, A., G. Milikh, Y. M. Yampolski, A. V. Koloskov, A. A. Sopin, A. Zalizovski, P. Pernhardt, S. Briczinski, C. Siefring, K. Chiang, Y. Morton, S. Taylor, A. Mahmoudian, W. Bristow, M. Rohoniemi, and K. Kapadopoulos, Studies of the ionospheric turbulence excited by the fourth gyroharmonic at HAARP, J. Geophy. Res., Space Sci., 120(8), , Prikryl, P., R. Ghoddousi-Fard, E. Thomas, J. Ruohoniemi, S. Shepherd, P. Jayachandran, D. Danskin, E. Spanswick, Y. Zhang, Y. Jiao, Y. Morton, GPS phase scintillation at high latitudes during geomagnetic storms of 7-17 March 2012 Part 1: The North American sector, Ann. Geophy., 33(6), , Prikryl, P., R. Ghoddousi-Fard, L. Spogli, C. Mitchell, G. Li, B. Ning, P. Cilliers, V. Sreeja, M. Aquino, M. Terkildsen, P. Jayachandran, Y. Jiao,Y. Morton, J. Ruohoniemi, E. G. Thomas, Y. Zhang, A. Weatherwax, L. Alfonsi, G. De Franceschi, V. Romano, GPS phase scintillation at high latitudes during geomagnetic storms of 7-17 March 2012 Part 2: Interhemispheric comparison, Ann. Geophy., doi: /2015JA021341, Slide 29

30 Conclusions GNSS has demonstrated to offer a low cost, passive, distributed means to sense ionospheric activities Conventional navigation receivers are not suitable for ionospheric monitoring: but alternative designs are achievable More correlative studies of common volume events using GNSS and other instruments on the ground and in space are needed to provide quantitative relationship/association among different mechanisms driving space weather activities. Slide 30

31 Acknowledgements Funding support from: AFOSR, AFRL, Colorado State University Collaborators: Charles Rino, Charles Carrano, Robert Robinson. Research facilities: Poker Flat Rocket Range, HAARP Students: Harrison Bourne, Brian Breitsch, Ian Collett, Jack Hall, Greg Myer, Yu Jiao, Dongyang Xu, Jun Wang, Steve Taylor Slide 31

32 Backup Slides Slide 32

33 GNSS Measurement Models Code phase: Carrier phase: r f = r +dr I_ f +dr other +e r f f f = r -dr I_ f +df other +e f f + Nl f Absolute, noisy Relative, accurate Means to mitigate other errors: Differencing Modeling Filtering Calibration Correction Services Exploitation of code and carrier synergy Carrier differencing: Df f 1 f 2 = f f 1 -f f 2 = c f 1 f 2 TEC + Db f 1 f 2 + ( N f 1 l f 1 - N f 2 l ) f 2 + De f 1 f 2 Code-minus-carrier: CMC f = r f -f f = c f TEC - N f l f +de f Slide 33

34 Triple Frequency TEC Estimation Df 12 Df 15 CMC 1 CMC 2 CMC 5 ( t) = c 12 TEC ( t) + ( l 1 N 1 - l 2 N 2 ) +Db 12 ( t) = c 15 TEC(t)+ ( l 1 N 1 - l 5 N 5 ) +Db 15 ( t) = c 1 TEC(t)- l 1 N 1 ( t) = c 2 TEC ( t) - l 2 N 2 ( t) = c 5 TEC ( t) - l 5 N 5 ( ( ) = c 12 TEC ( t +1) + ( l 1 N 1 - l 2 N 2 ) + Db 12 ) = c 15 TEC(t +1)+ ( l 1 N 1 - l 5 N 5 ) +Db 15 ( ) = c 1 TEC(t +1)- l 1 N 1 ( ( ) = c 2 TEC ( t +1) - l 2 N 2 ) = c 5 TEC ( t +1) - l 5 N 5 Df 12 t +1 Df 15 t +1 CMC 1 t +1 CMC 2 t +1 CMC 5 t +1 =A.. Slide 34

35 Triple Frequency TEC Estimation Example Alaska (Lat 65.12, Lon ) Multipath Multipath Real ionosphere structures Slide 35

36 Ionosphere Structure vs. Multipath Ionosphere structures Multipath Slide 36

37 TEC Estimation Observations Synchronization across different frequency combinations: Ionosphere structures: in-sync across all combinations Multipath: not in-sync. Relative bias drifts among different frequency combinations: May be due to hardware bias changes Can be used to estimate the hardware bias changes L2 L5 combination amplifies multipath effects Maybe used to estimate multipath Slide 37

38 Missing Measurements in ISM Receivers Slide 38

39 Findings: Frequency Diversity Response Slide 39

Morton, Automatic equatorial GPS amplitude scintillation using

40 How to Create An Event Trigger? Neyman-Pearson (NP) Support Vector Machine Y. Jiao, J. Hall, Y. Morton, Automatic equatorial GPS amplitude scintillation using machine learning, IEEE Trans. Aero. Elec. Sys., TAES Y. Jiao, J. Hall, Y. Morton, Performance evaluation of an automatic GPS ionospheric phase scintillation detector using a machine learning algorithm, to appear, Navigation. Support vectors Slide 40

41 How Do We Process Data: Semi-Open Loop Architecture From Sampling device Correlators Quality indicator Good Not good Estimators Filters Signal parameters Reference Generation From ephemeris Prior knowledge From unaffected SV Doppler/range change prediction SV orbit RX position Time For dynamic platforms, compute from unaffected SVs Vector processing Slide 41

42 Dilemma: GNSS for Ionosphere Monitoring GNSS Monitoring Receivers Understanding Space Weather Effects High Quality Data Slide 42

43 Decent Match Slide 43

44 No ASI Slide 44

45 ASI is Cloudy Slide 45

46 No GNSS Slide 46

High-latitude & Equatorial Ionospheric Scintillation Based on An Event-Driven Multi-GNSS Data Collection System

High-latitude & Equatorial Ionospheric Scintillation Based on An Event-Driven Multi-GNSS Data Collection System Jade Morton, Yu Jiao, Steve Taylor Electrical and Computer Engineering Department Colorado