DEVELOPMENT OF Open Source COMPASS SDR

Transcription

1 1 P a g e DEVELOPMENT OF Open Source COMPASS SDR Submitted by:- JAY PRAKASH and Adarsh Khandelwal B Tech, Part IV Electronics Engineering, IIT (BHU)

2 An OpenSource COMPASS/BEIDOU Software Defined Receiver A DESERTATION SUBMITTED AS PARTIAL FULFILLMENT OF REQUIREMENT OF THE AWARD OF DEGREE BACHELOR OF TECHNOLOGY IN ELECTRONICS ENGINEERING UNDER THE GUIDANCE OF SUPERVISOR: Dr. K.P.SINGH SUBMITTED BY JAY PRAKASH (09105EN028) ADARSH KHANDELWAL (09105EN035) DEPARTMENT OF ELECTRONICS ENGINEERING INDIAN INSTITUTE OF TECHNOLOGY (BHU), VARANASI.

3 CONTENTS 1. Summary 2.1 Need of Compass SDR 2.2BeiDou System Overview 2.3 Receiver Architecture 3.1 Signal processing 3.2 Acquisition 3.3 Tracking 3.4 Navigation data decoding 3.5 Transformation from PZ90.02 to WGS84 3. Final navigation solution 4. Bibliography

4 SUMMARY Software-defined radio receivers (SDR) is a concept for transceivers in which the signal processing is accomplished via a programmable general-purpose microprocessor or digital signal processor (DSP), as opposed to an applicationspecific integrated circuit (ASIC). A software receiver differs from a hardware receiver by performing correlations in software running on a general purpose microprocessor. It can afford batch data processing options that are not available in hardware implementations. New frequencies and new pseudorandom number (PRN) codes can be used simply by making software changes. SDR are not only research tools for the development and test of new navigation and positioning algorithms. The flexibility of software architectures enables them to record several pieces of information that are not limited to position and velocity. Correlator and discriminator outputs, frequency and phase lock indicators and several synchronization messages are just a few examples of the parameters that a software receiver makes available to users and researchers. And the software receiver could be reprogrammed to adjust a new navigation system, which provides an added benefit from the use of the software radio architecture. Along with the decrease of the required processing time, the high configurability, high development speed, low cost software receiver is obtaining more people's favors. In this paper, a complete Intermediate Frequency (IF) Software COMPASS Receiver was developed using matlab code. It can be used for acquisition, tracking, and calculating position for the COMPASS B1I and B2I signals. Then after multi-core programming capability of Matlab have been exploited to insure parallel processing for three constellation and combining the results using proper algorithms for more precise coordinates.

5 Need of the SDR Perfect and precise positioning have always been a thing of importance be it for military purposes, civilian usage or navigation (indoor and aircrafts).with advent of newer constellations in the group:-glonass,galileo,compass,gagan and many more to come in the list we can be assured of getting unparallel accuracy and precision. There are two points of concern:- 1. Designing Software Defined Receiver for Compass as they have insured minimum no of satellite in the constellation ie 4.This will insure better PVT results in combination with other available constellations forming an augmented receiver. After acquisition and tracking have been done it would be mainly focusing on decoding of data and finding pseudo-ranges and PVT solutions. 2. As the hardware receiver designs are not open source and non-reconfigurable, software base gives lots of freedom to each user to change algorithms at any level in the highly modular structure of the receiver. This project shall benefit numerous researchers, students and developers around the world in understanding the core working of GNSS acquisition, tracking and post-navigation processing of the raw GNSS samples. We well know we need to constantly update and change algorithms to achieve more better results and design a robust model in itself. With such a large pool of GNSS researchers and open source contributors something know to all and within reach can help in rigorous and dynamic updates of the model we are developing. Each could add with changes and see if results improve in varied conditions. The platform shall seek mutual development be it in signal processing, algorithms or architectural modifications. Finally we would have a model being worked upon by hundreds and thousands of minds and the GNSS would not be a thing of industries and high end institutions but within reach of civilians and then can configure whatever and whenever they want. Ultimately we have a full fledge receiver to get PVT solutions using varied constellations. Applications of Compass are equivalent to those of GPS and other constellations and can be seen mostly in highly precise navigation of land, sea, air and low orbiting spacecraft.besides this, Compass is also suitable for the dissemination of highly precise global and local time scales as well as for establishing global geodetic coordinate systems and local geodetic networks. The system can also be used for providing precise coordinates for cadastre works. Further usage could contain the support of research work in geology, geophysics, geodynamics, oceanography and others by providing position and time information. Similar uses are possible for large scale construction projects.

6 With this range of applications and the achievable accuracy, Compass has become an attractive tool for navigational and geodetic purposes. But not only Compass as a stand-alone system draws the interest of scientists around the world. The fact that there are two independent, but generally very similar satellite navigation systems also draws attention to the combined use of both systems. This combined use brings up a number of advantages. At first, the number of observable satellites is increased with respect to one single system. This will provide a user with a better satellite geometry and more redundant information, allowing him to compute a more accurate position fix. In cases with obstructed visibility of the sky, such as mountainous or urban areas, a position fix might not be possible at all without these additional satellites. Besides that, the more satellite measurements are available, the earlier and more reliably a user can detect and isolate measurement outliers or even malfunctioning satellites. Thus, the combined use of GPS, Compass, Galileo and GLONASS may aid in Receiver Autonomous Integrity Monitoring (RAIM), providing better integrity of the position fix than a single system alone.

7 BeiDou System Overview Space Constellation BeiDou Navigation Satellite System is called BeiDou System for short,with the abbreviation as BDS. When fully deployed, the space constellation of BDS consists of five Geostationary Earth Orbit (GEO) satellites, twenty-seven Medium Earth Orbit (MEO) satellites and three Inclined Geosynchronous Satellite Orbit (IGSO) satellites. The GEO satellites are operating in orbit at an altitude of 35,786 kilometers and positioned at E, 80 E, E, 140 E and 160 E respectively. The MEO satellites are operating in orbit at an altitude of 21,528 kilometers and an inclination of 55 to the equatorial plane. The IGSO satellites are operating in orbit at an altitude of 35,786 kilometers and an inclination of 55 to the equatorial plane. By the end of 2012, there are five GEO, four MEO and five IGSO BeiDou navigation satellites in orbit. Coordinate System BDS adopts the China Geodetic Coordinate System 2000 (CGCS2000), and the definition is listed below: The origin is located at the mass center of the Earth; The Z-axis is in the direction of the IERS (International Earth Rotation and Reference System Service) Reference Pole (IRP); The X-axis is directed to the intersection of IERS Reference Meridian (IRM) and the plane passing the origin and normal to the Z-axis; The Y-axis, together with Z-axis and X-axis, constitutes a right handed orthogonal coordinate system. The origin of the CGCS2000 is also the geometric center of the CGCS2000 ellipsoid, and the Z-axis is the rotation axis of the CGCS2000 ellipsoid. The parameters of the CGCS2000 ellipsoid are as follows: Semi-major axis: a = m Geocentric gravitational constant (mass of the earth atmosphere included): μ = *10^14 Flattening: f = 1/ Rate of earth rotation: *10^-5

8 Time System The time reference for the BDS uses the BeiDou navigation satellite system Time (BDT). BDT adopts international system of units (SI) seconds, rather than leap seconds, as the basic unit for continuous accumulation. The start epoch of BDT was 00:00:00 on January 1, 2006 of Coordinated Universal Time (UTC). BDT is counted with week and seconds of week (SOW). BDT is related to the UTC through UTC(NTSC). BDT offset with respect to UTC is controlled within 100 nanoseconds (modulo 1 second). The leap seconds are broadcast in navigation (NAV) message. Signal Specifications Signal Structure The B1 signal is the sum of channel I and Q which are in phase quadrature of each other. The ranging code and NAV message are modulated on carrier. The signal is composed of the carrier frequency, ranging code and NAV message. The B1 signal is expressed as follows:

9 Signal Characteristics 1. Carrier Frequency The nominal frequency of B1I signal is MHz. 2. Modulation Mode The transmitted signal is modulated by Quadrature Phase Shift Keying (QPSK). 3. Carrier Phase Noise The phase noise spectral density of the unmodulated carrier is as follows: 4. Signal Multiplexing Mode The signal multiplexing mode is Code Division Multiple Access (CDMA). 5. Satellite Signal Bandwidth and Out-band Suppression (1)Bandwidth (1 db): MHz (centered at carrier frequency of B1I); Bandwidth (3 db): 16 MHz (centered at carrier frequency of B1I). (2)Out-band suppression: no less than 15 db on f 0 ±30 MHz, where f 0 is the carrier frequency of B1I signal. 6. Spurious In-band spurious shall be at least 50 db below the unmodulated carrier of B1I over the satellite signal bandwidth (1 db). 7. Signal Coherence (1) The random jitter of the initial phase difference between the ranging code modulated on carrier and carrier is less than 3 (1σ) (relative to the carrier) for B1I signal. (2) Carrier phase quadrature difference between channel I and Q is less than 5 (1σ).

10 8. Equipment Group Delay Differential Equipment group delay is defined as the delay between the antenna phase center of a satellite and the output of the satellite onboard frequency source. The equipment group delay differential of B1I is given as T GD1 in NAV message with uncertainty less than 1 nanosecond (1σ). 9. Ranging Code on B1I The chip rate of the B1I ranging code is Mcps, and the length is 2046 chips. The B1I ranging code (hereinafter referred to as C B1I ) is a balanced Gold code truncated with the last one chip. The Gold code is generated by means of Modulo-2 addition of G1 and G2 sequences which are respectively derived from two 11-bit linear shift registers. The generator polynomials for G1 and G2 are as follows: The different phase shift of G2 sequence is accomplished by respective tapping in the shift register generating G2 sequence. By means of Modulo-2 addition of G2 with different phase shift and G1, a ranging code is generated for each satellite.

11 The phase assignment of G2 sequence is shown:-

12 Receiver Architecture Antenna Pre Amplifier Down Converter IF Sampling Tracking Loop Navigation message Extraction Measurements Navigation Solution It consists of five modules: an antenna, a RF front-end, acquisition module, n receiver channels and position calculation module. The antenna and RF front-end devices are the only hardware devices of the system. The RF front-end device is necessary to down convert the COMPASS signal to an intermediate frequency (IF), sample the IF signal and digitize it. The present CPU capacity is still unable to process the COMPASS signal directly from the antenna in completely software-based approach. Thus a RF front-end device is still necessary. In conventional hardware-based receiver, the three blocks in the dashed textbox in Figure are implemented in an IC chip and hence the user does not have a free access to the algorithms built inside the chips. In software-based receiver, these blocks are fully implemented using high level programming languages and hence the user has complete control over the algorithms. This is the main difference between the software receiver and a conventional hardware receiver. The acquisition module mainly complete three tasks: finding satellites visible to the receiver, finding coarse values for B1 code or B2 code phase and carrier frequency for each satellite. A receiver channel includes six functional blocks: code tracking, carrier tracking, bit synchronization, navigation data decoding, satellite position calculating and pseudo-range calculating, as shown in Figure 2. The detail description of each functional block can be found in references.

13 COMPASS SDR The final goal of a GNSS receiver is computing the position and velocity of the receiver or at least providing some measurements which can be used to compute these values. For this purpose, the received signals at antenna must be acquired and tracked. After tracking, navigation message can be extracted and utilized to generate some measurements that are useful in computing the navigation solution. Plot of raw data obtained from frontend

14 Signal Processing The received signal at the antenna is amplified and then down converted to the desired intermediate frequency (IF). The down converted signal is sampled and sent to the signal processor block. Amplification, down conversion and sampling are performed in the radio frequency (RF) front-end block. The signal processor block consists of tracking loop as well as navigation message extraction and measurement generation components. One signal processing block is assigned for each satellite signal being tracked and is herein simply called a channel. Generally, a signal tracking loop consists of the following components. Doppler removal component in which the carrier part of the received signal is removed Correlation component in which the ranging code part of the received signal is removed Discriminator component which can compute the difference (error) between the locally generated signals and the received ones Loop filter component which smoothes the output of the discriminators Timing and clock management The receiver was designed to work with different sampling rates and sampling resolutions. The fundamental receiver timing reference, used to time-stamp the signal reception time, is established by synchronizing a receiver clock using the first sample of data in a given subframe. The COMPASS time of this sub-frame boundary is transmitted in the navigation data message and effectively allows the locally maintained, data sample based, receiver clock to be set relatively accurately with respect to COMPASS time. However, this internal receiver clock will not be exactly synchronized to COMPASS time and must be constantly corrected using the output of the position solution. The inexact frequency of the sampled data will cause the signal receive time to contain a bias with respect to COMPASS time. However, by constantly correcting the receiver time as part of the navigation solution and propagating it forward as new data is read in based on the data sample frequency, it can be maintained close enough to COMPASS system time to make measurements. The second half of the timing problem is determining the time of transmission of the satellite signals at a given data sample. The receiver recorded the exact sample where the satellite sub-frame was identified. The time at this sub-frame obtained from the navigation data, combined with data bits and 1-ms-code epochs allows the receiver to calculate the signal transmission time at any sample. This is successful due to the very accurate clocks generating the signals on board the satellites.

15 Main processing loop The startup and main processing modules are shown in Figure. These do not represent individual functions but the high-level processing states that the receiver progresses through, ultimately advancing to the navigation state, where the receiver PVT is estimated. The initialization of the receiver consists primarily of reading the configuration file, initializing internal variables and performing miscellaneous set up tasks. The initialization sequence is only executed once for every run of the receiver. PostProcessing.m Ask for data file Create data vectors Acquisition.m Frequency and code Phase for each satellite Tracking.m Prompt I and sample no For each satellite after tracking acquired satellites postnavigation.m Positions solutions End Flow diagram for COMPASS SDR

16 ACQUISITION The acquisition functions of the receiver were designed to be flexible. An outline of the acquisition processing is shown in Figure. The acquisition steps of the receiver are as follows: (1) Gather a reasonable amount of data for use in the FFT acquisition processing. The default value is currently 4 ms of data samples. (2) When enough data has been collected, call the acquire function, specifying the satellite to search for and scan over a wide range of coarse Doppler bins by performing the following steps: a) Perform FFT on input sample buffer. b) b)multiply sample FFT and pre-calculated PRN code FFT; c) Perform inverse FFT;d) Search for peaks exceeding the detection threshold. (3) If a satellite signal is found, then: a) Perform fine Doppler search and store results; b) Perform debug searches if specified in the configuration file; c) Allocate it to a tracking channel.

17 The flow chart of the algorithm is as shown below: Acquisition.m Read input signal Create two vectors of data (Signal1 and signal2) Loop initialisation PRN = 1:no of satellites Loop initialisation j = 1:no of freq bins Generate local signals Remove carrier signal & convert to freq domain Correlate with Range code (multiply in freq domain) See for maximum power and store for bin Look for Correlation peak and store carrier frequency Find code phase of the same correlation peak Find the second highest correlation peak If peakmetric>threshold Store acqres for PRN

18 Acquisition Result Plot Acquisition Metric was compared to a predefined empirical value of 3 and satellites with values greater than 3 were tracked using tracking.m file. Acquired Satellites Channel nos.:

19 TRACKING Tracking loop overview The objective of a tracking loop is determining the difference between the locally generated signal and the incoming pseudo-base-band signal, filtering that estimate and sending new information to the signal generators. In a tracking loop process, both carrier and code signals are accurately reproduced inside the receiver. For each carrier and code portion of the received signal, a tracking loop exists. The code tracking loop is called a delay lock loop (DLL) and must provide an estimate of code phase of the ranging code being tracked. The carrier tracking loop is called carrier lock loop (CLL) and it must track the incoming carrier phase via a phase lock loop (PLL) or a carrier frequency via frequency lock loop (FLL). The carrier phase yields more accurate information needed for navigation message decoding. Two tracking loops can be coupled in some cases where the DLL needs an accurate estimate of the incoming carrier frequency which the CLL can provide. Tracking algorithm for GLONASS is similar to that of the GPS with no major changes as such. The prime importance is using different carrier frequencies (obtained from acquisition.m in acqresults structure) in PLL for each tracking channel. And codes would remain same for all DLL loops unlike GPS though they will be of three types:-e(early),p(prompt) and D(delay) like GPS. Phase lock loop The objective of a phase lock loop (PLL) is to generate the carrier portion of the locally generated signal. The discriminator in phase lock loop determines the difference between the phase of the locally generated carrier signal and the received pseudo-base-band signal. The output of the discriminator is sent to the NCO to generate a new reference signal. In Figure 4-3, the carrier tracking loop is highlighted with green color. PLL is sensitive to data bit transitions. Specifically, when the navigation data bit changes from one to zero or from zero to one, a 180 phase change is detected by the PLL and it therefore attempts to correct the perceived error. As such, a discriminator that is insensitive to bit transitions is preferred. These types of discriminators are termed Costas discriminators. In Costas discriminators, Doppler removed and correlated I channel and Q channel are used. The PLL discriminator used for GLONASS phase lock loop is a two-quadrant arctangent Costas discriminator. Delay lock loop The objective of a delay lock loop (DLL) is to track the standard ranging code of the received pseudobase-band signal by generating a local standard ranging code. This loop consists of correlator, accumulator, DLL discriminator and loop filter.the inputs to the DLL are Doppler removed samples modulated with navigation data and ranging code. To remove this ranging code, it is required to generate three pairs of I and Q values; early (IE, QE), prompt or punctual (IP, QP), and late (IL, QL), where E, P, and L subscripts stand for early, punctual and laterespectively. Early and late values are typically one chip away from each other and are half chip spaced from the prompt value.there are two types of DLL discriminators: 1. Coherent discriminator: where all power is on I channel, implying phase lock is achieved. 2. Non-coherent discriminator: where phase lock is not required. Loop filters The objective of a loop filter is to reduce the effect of noise on the discriminator output signal in order to generate an accurate and smooth estimate of the original signal at its output and to pass this information to the NCO. A loop filter rejects as much noise as possible and responds to the changes in

20 signals which are caused by both receiver and satellite dynamics (Ward et al 2006). Satellites dynamics cause Doppler changes up to 0.9 Hz/s and receiver dynamics causes additional changes, wither higher acceleration causing faster changes in Doppler.The loop filter order and noise bandwidth are two main parameters of a loop filter. By carefully choosing these parameters, the performance of a tracking loop can increase significantly. Integrate +Dump Integrate +Dump Integrate +Dump Incoming Signal PRN Code Generator Code Loop Discriminator Integrate +Dump Integrate +Dump 90 Integrate +Dump NCO Carrier generator Carrier Loop Filter Carrier Loop Discriminator The block diagram of a complete tracking channel on the GLONASS receiver. The software correlator has the task of generating the code and carrier replica signals and performing the necessary correlations and accumulations needed to feed into the tracking functions. When the number of samples processed is equal to a complete code period (1 ms for COMPASS B1/B2 code) the tracking loop function is called. The correlator continually computes results on six separate correlator spacings for each channel at every sample. These include prompt correlators for the in-phase

21 (I) and quadrature (Q) signals components, as well as early and late offset correlators for each. The early and later correlators are spaced one-half chip from the prompt value, and are used primarily in calculating the tracking loop feedback values. At the start of each pass through the tracking loops, the accumulated correlator measurements are used to calculate an error in the replica signal alignment, which is then used to adjust the carrier and code increments used in the correlator for the next set of samples. The tracking error is determined using a discriminator function based on a combination of the six available accumulations calculated for each channel by the software correlator function. This discriminator value is used to calculate new values for the code and carrier increments, which are then fed back into the carrier and code replica generator to be applied during the next correlation interval. TRACK RESULT Afore shown Plot shows the navigation bits extracted by tracking.m program along with PLL and DLL Discriminators plots. Magnified view of the navigation message clearly showing data bits which can now be extracted by postnavigation.m

22 NAVIGATION DATA DECODING NAV Message Classification NAV messages are formatted in D1 and D2 based on their rate and structure. The rate of D1 NAV message which is modulated with 1 kbps secondary code is 50 bps. D1 NAV message contains basic NAV information (fundamental NAV information of the broadcasting satellites, almanac information for all satellites as well as the time offsets from other systems); while D2 NAV message contains basic NAV and augmentation service information (the BDS integrity, differential and ionospheric grid information) and its rate is 500 bps.the NAV message broadcast by MEO/IGSO and GEO satellites is D1 and D2 respectively. Data Error Correction Coding Mode The NAV message encoding involves both error control of BCH(15,11,1) and interleaving. The BCH code is 15 bits long with 11 information bits and error correction capability of 1 bit. The generator polynomial is g(x)=x^4+x+1. The NAV message bits are grouped every 11 bits in sequence first. The serial/parallel conversion is made and the BCH(15,11,1) error correction encoding is performed in parallel. Parallel/serial conversion is then carried out for every two parallel blocks of BCH codes by turns of 1 bit to form an interleaved code of 30 bits length. The implementation is shown D1 NAV Message Secondary Code Modulated on D1 For D1 NAV message in format D1 of rate 50 bps a secondary code of Neumann- Hoffman (NH) code is modulated on ranging code. The period of NH code is selected as long as the duration of a NAV message bit. The bit duration of NH code is the same as one period of the ranging code. Shown as in Figure, the duration of one NAV message bit is 20 milliseconds and the ranging code period is 1 millisecond. Thus the NH code (0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0) with length of 20 bits, rate 1 kbps and bit duration of 1 millisecond is adopted. It is modulated on the ranging code synchronously with NAV message bit.

23 D1 NAV Message Frame Structure The NAV message in format D1 is structured in the superframe, frame and subframe. Every superframe has bits and lasts 12 minutes. Every superframe is composed of 24 frames (24 pages). Every frame has 1500 bits and lasts 30 seconds. Every frame is composed of 5 subframes. Every subframe has 300 bits and lasts 6 seconds. Every subframe is composed of 10 words. Every word has 30 bits and lasts 0.6 second. Every word consists of NAV message data and parity bits. In the first word of every subframe, the first 15 bits is not encoded and the following 11 bits are encoded in BCH(15,11,1) for error correction. So there is only one group of BCH code contained and there are altogether 26 information bits in the word. For all the other 9 words in the subframe both BCH(15,11,1) encoding for error control and interleaving are involved. Each of the 9 words of 30 bits contains two blocks of BCH codes and there are altogether 22 information bits in it.

24 Corresponding program responsible for decoding and finding navigation solution:- TrackResults postnavigation.m Settings Find Preambles For i=1:activechnanellist Copy 15 strings long record from tracking output Decode Data and Extract ephemeris info Initialise current measurement calculatepseudoranges Find satellite position and clock offset Calculate LeastSquarePos Receiver Position Transform from PZ90.02 to WGS84 Coordinate conversion Store Results Flow Diagram for postnavigation.m

25 Functions included in postnavigation.m are:- findpreambles.m ephemeris.m satposg.m calculatepseudoranges.m leastsquarepos.m satclkcorr.m cart2geo.m cart2utm.m These functions are included in Appendix. A brief overview is as follows. FindPreambles.m:- It finds the first Time Mark occurrence in the bit stream of each channel. The Time Mark is a unique bit sequence At the same time function returns list of channels, that are in tracking state. Basically tracking output from each channels are correlated with timemarks and positions of timemarks are found by comparing absolute value of correlation to a threshold value.the process thus gives position of timemarks for each channel and mean while keeps track of active channel list too.

26 Ephemeris.m:- It decodes ephemerides and time of frame start from the given bit stream. The stream (array) in the parameter DATA must contain bits. The first element in the array must be the first bit of a string. The string number of the first string in the array is not important. ALGORITHM:- Ephemeris.m(for each channel ) For i=1:15 (for 15 strings) 85 bits out of 15 strings taken from Take 85 data bits trackresults(channelnr).i_p(subframestart(channelnr) : subframestart(channelnr) (1500 * 20) -1) Read last four bits of m word to find string no. Corresponding to ICD Table no:4.4 and 4.5 As per decoded value of m (either of 1:5 of m ie string no) get corresponding ephemeris parameters Only 5 first strings are of interest. The rest strings contain almanac that is not used in this program.

27 Satposg.m:- This function calculates initial position, velocity and acceleration of the satellites in prnlist on the transmit Time based on ephemeris data (eph). Based on CALCULATIONS FOR POSITIONING WITH THE GLOBAL NAVIGATION SATELLITE SYSTEM by Chao-heh Cheng August, 1998 Transmit time (TOW) Algorithm Satposg.m Active PRN List Ephemeris Data For i=1:no. length(prnlist) Delta time between ephemeris issue time and current time. Divide calculation into subintervals Initialize constants (c 20, u, a e, J) Integration of equations in direct absolute geocentric coordinate system using 4 th order Runga-Kutta technique as given in GLONASS ICD(Appendix 3) Obtain position velocity acceleration and clock-error Flow diagram of satposg.m

28 CalculatePseudoranges.m:- CalculatePseudoranges finds relative pseudoranges for all satellites listed in Channel List at the specified millisecond of the processed signal. The pseudoranges contain unknown receiver clock offset. Track results CalculatePseudoranges.m Settings Channel List For i= 1: length(channel list) Calculate the travel time Truncate the traveltime and compute pseudoranges Convert travel time to a distance Flow diagram for CalculatePseudoranges.m LeastSquarePos.m:- This Function calculates the Least Square Solution for Receiver s Position Input:- satpos obs settings - Satellites positions (in ECEF system: [X; Y; Z;] -one column per satellite) - Observations - the pseudorange measurements to each satellite: (e.g. [ ]) - receiver settings Outputs:- pos - receiver position and receiver clock error (in ECEF system: [X, Y, Z, dt]) el - Satellites elevation angles (degrees) az - Satellites azimuth angles (degrees) dop - Dilutions Of Precision ([GDOP PDOP HDOP VDOP TDOP]) The concerned algorithm is similar to that of GPS SDR exactly.

29 Transformation from PZ90.02 to WGS84. After calculation of Receiver position using LeastSquarePos.m it was needed to transform from PZ90.02 to WGS84. satellites broadcast their positions in PZ-90 coordinates as a part of their navigation messages. The navigation message is broadcast by each satellite and usually refreshed every half-hour. The PZ-90 geocentric coordinate frame, specified as an abstract mathematical entity, is just one element of an overall reference system to represent the earth from geometric, gravitational, and geodetic standpoints. Like its counterpart, WGS84 for GPS, PZ-90 is a self-contained and self-consistent system within which to define a 3-D position. A comprehensive description of WGS84 is available from National Imagery and Mapping Agency (NIMA) reports and the description of PZ-90 comes mainly from the GLONASS Interface Control Document.The values of the defining parameters for the PZ-90 gravity model and its ellipsoid are slightly different from those of WGS84. These differences, however, are easily accommodated. A more difficult problem arises from the differences in the ECEF coordinate frames. The ECEF coordinate frames of WGS84 and PZ-90 differ in their formal definitions. While each locates the origin at the center of mass of the earth, the directions of the z axes are different: WGS84 defines it as passing through the instantaneous pole of 1984; PZ-90 adopts instead the average position of the pole between the years 1900 and This description, however, is not adequate as a basis for determining a transformation between GPS and GLONASS. Actually, even if the formal definitions were identical, it would not have ensured that the coordinates of a point as determined by measurements from the two systems would be identical. The coordinate frame for each system is realized (or, implemented) by adopting the coordinates of a set of stations. A consistent set of such coordinates defines implicitly the ECEF coordinate frame (i.e., an origin, a set of directions for the Cartesian axes, and a scale factor). Therefore, even if GPS and GLONASS had adopted the same definition for the reference coordinate frame, the independent implementation of each system would have kept the two from being identical. A transformation between PZ-90 and WGS84, the coordinate frames used by GLONASS and GPS, respectively, has been studied and implemented in combining measurements from the two systems [29]. From the research results of Lincoln Laboratory, the difference between the two coordinate frames is that the zero meridian (X-axis) of PZ-90 is East of that for WGS84. A small clockwise rotation of 0.4 seconds of arc of the Z-axis of PZ-90 brings the two coordinate frames substantially into coincidence. The residuals are reduced further, though only slightly, by a 2.5 m displacement of the origin along the Y-axis. As shown in Figure 4.1, the estimated transformation between PZ-90 (u, v, w) and WGS84 (x, y, z) is: x x u = Y 1.96x v Z w

30 Final Navigation solution

31 Bibliography 1. K. Borre, D.M. Akos, N. Bertelsen, P. Rinder, and S.H. Jensen: A Software-Defined GPS and Galileo Receiver (ISBN ) 2. Saloomeh Abbasiannik, Multichannel Dual Frequency GLONASS Software Receiver in Combination with GPS L1 C/A (URL: April Kai Borre, Aalborg University, Dennis Akos, University of Colorado, A Software-Defined GPS and Galileo Receiver: Single-Frequency Approach 4. Chao-heh Cheng; CALCULATIONS FOR POSITIONING WITH THE GLOBAL NAVIGATION SATELLITE SYSTEM a Thesis Presented to The Faculty of the Fritz J. and Dolores H. Russ College of Engineering and Technology Ohio University in Partial Fulfillment Of the Requirement for the Degree Master of Science, August, 1998

32 Appendix:- 1. Acquisition code function acqresults = acquisition(longsignal, settings) %Function performs cold start acquisition on the collected "data". It %searches for COMPASS signals of all satellites, which are listed in field %"acqsatellitelist" in the settings structure. Function saves code phase %and frequency of the detected signals in the "acqresults" structure. % %acqresults = acquisition(longsignal, settings) % % Inputs: % longsignal - 11 ms of raw signal from the front-end % settings - Receiver settings. Provides information about % sampling and intermediate frequencies and other % parameters including the list of the satellites to % be acquired. % Outputs: % acqresults - Function saves code phases and frequencies of the % detected signals in the "acqresults" structure. The % field "carrfreq" is set to 0 if the signal is not % detected for the given PRN number. % % Initialization ========================================================= % Find number of samples per spreading code samplespercode = round(settings.samplingfreq /... (settings.codefreqbasis / settings.codelength)); % Create two "settings.acqcohintegration" msec vectors of data % to correlate with: signal1 = longsignal(1:2*samplespercode); % Find sampling period: ts = 1 / settings.samplingfreq; % Find phase points of the local carrier wave: phasepoints = (0 : (2*samplesPerCode-1)) * 2*pi*ts; % Number of the frequency bins for the given acquisition band numberoffrqbins = round(settings.acqsearchband * 2*1) + 1; % Generate all C/A codes and sample them according to the sampling freq: cacodestable = makecatable(settings); %--- Initialize arrays to speed up the code % Search results of all frequency bins and code shifts (for one satellite) results = zeros(numberoffrqbins, 1*samplesPerCode); % Carrier frequencies of the frequency bins frqbins = zeros(1, numberoffrqbins); %--- Initialize acqresults % Carrier frequencies of detected signals acqresults.carrfreq = zeros(1, 37); % C/A code phases of detected signals acqresults.codephase = zeros(1, 37);

33 % Correlation peak ratios of the detected signals acqresults.peakmetric = zeros(1, 37); fprintf('('); % Perform search for all listed PRN numbers... for PRN = settings.acqsatellitelist % Correlate signals ====================================================== %--- Perform DFT of C/A code %Multiply C/A code on Neumann-Hoffman code (first 5 ms - otherwise too long wait time) %NH = "0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0"; cacodefreqdom = conj(fft([cacodestable(prn, :) zeros(1, samplespercode)])); %--- Make the correlation for whole frequency band (for all freq. bins) for frqbinindex = 1:numberOfFrqBins %--- Generate carrier wave frequency grid (freqency step depends % on "settings.acqcohintegration") frqbins(frqbinindex) = settings.if -... (settings.acqsearchband/2) * (1000 / (2*1)) * (frqbinindex - 1); %--- Generate local sine and cosine sigcarr = exp(1i*frqbins(frqbinindex) * phasepoints); %% a=length(sigcarr); %% fprintf('length os sigcarr is:%d',a); %% fprintf('samples per code is: %d',samplespercode); %--- "Remove carrier" from the signal and Convert the baseband % signal to frequency domain %pause; IQfreqDom1 = fft(sigcarr.* signal1); %--- Multiplication in the frequency domain (correlation in time domain) convcodeiq1 = IQfreqDom1.* cacodefreqdom; %--- Perform inverse DFT and store correlation results acqres1 = abs(ifft(convcodeiq1)).^ 2; %--- Check which msec had the greater power and save that, will %"blend" 1st and 2nd "settings.acqcohintegration" msec but will % correct data bit issues results(frqbinindex, :) = acqres1(1:samplespercode); end % frqbinindex = 1:numberOfFrqBins % Look for correlation peaks in the results ============================== % Find the highest peak and compare it to the second highest peak % The second peak is chosen not closer than 1 chip to the highest peak %--- Find the correlation peak and the carrier frequency [peaksize frequencybinindex] = max(max(results,[],2));

34 %--- Find code phase of the same correlation peak [peaksize codephase] = max(max(results)); %--- Find 1 chip wide CA code phase exclude range around the peak ---- samplespercodechip = round(settings.samplingfreq /... settings.codefreqbasis); excluderangeindex1 = codephase - samplespercodechip; excluderangeindex2 = codephase + samplespercodechip; %--- Correct C/A code phase exclude range if the range includes array %boundaries if excluderangeindex1 < 2 codephaserange = excluderangeindex2 :... (samplespercode + excluderangeindex1); elseif excluderangeindex2 > samplespercode codephaserange = (excluderangeindex2 - samplespercode) :... excluderangeindex1; else codephaserange = [1:excludeRangeIndex1,... excluderangeindex2 : samplespercode]; end %--- Find the second highest correlation peak in the same freq. bin --- secondpeaksize = max(results(frequencybinindex, codephaserange)); %--- Store result acqresults.peakmetric(prn) = peaksize/secondpeaksize; % If the result is above threshold, then there is a signal... if (peaksize/secondpeaksize) > settings.acqthreshold %--- Indicate PRN number of the detected signal fprintf('%02d ', PRN); acqresults.codephase(prn) = codephase; acqresults.carrfreq(prn) =... settings.if -... (settings.acqsearchband/2) * (1000 / (2*1)) * (frequencybinindex - 1); else %--- No signal with this PRN fprintf('. '); end % if (peaksize/secondpeaksize) > settings.acqthreshold end % for PRN = satellitelist %=== Acquisition is over ================================================== fprintf(')\n'); end

35 2. Acquisition_4ms code function acqresults = acquisition_4x5ms(longsignal, settings) %Function performs cold start acquisition on the collected "data". It %searches for COMPASS signals of all satellites, which are listed in field %"acqsatellitelist" in the settings structure. Function saves code phase %and frequency of the detected signals in the "acqresults" structure. % %acqresults = acquisition(longsignal, settings) % % Inputs: % longsignal - 11 ms of raw signal from the front-end % settings - Receiver settings. Provides information about % sampling and intermediate frequencies and other % parameters including the list of the satellites to % be acquired. % Outputs: % acqresults - Function saves code phases and frequencies of the % detected signals in the "acqresults" structure. The % field "carrfreq" is set to 0 if the signal is not % detected for the given PRN number. % % Initialization ========================================================= % Find number of samples per spreading code samplespercode = round(settings.samplingfreq /... (settings.codefreqbasis / settings.codelength)); fprintf('%dsamplespercode=\n',samplespercode) %Let's test simple acceleration. Let's resample the signal to lower frequency. a=length(longsignal); fprintf('%d longsignal=\n',a); longsignal = reshape(longsignal, settings.acqresamplecoef,... length(longsignal) / settings.acqresamplecoef); %longsignal = sum(longsignal, 'r'); longsignal = sum(longsignal); samplespercode = samplespercode / settings.acqresamplecoef; % Create two "settings.acqcohintegration" msec vectors of data % to correlate with: signal1 = longsignal(0*5*samplespercode+1:5*samplespercode+1*5*samplespercode); signal2 = longsignal(1*5*samplespercode+1:5*samplespercode+2*5*samplespercode); signal3 = longsignal(2*5*samplespercode+1:5*samplespercode+3*5*samplespercode); signal4 = longsignal(3*5*samplespercode+1:5*samplespercode+4*5*samplespercode); % Find sampling period: ts = settings.acqresamplecoef / settings.samplingfreq;

36 % Find phase points of the local carrier wave: phasepoints = (0 : (10*samplesPerCode-1)) * 2*pi*ts; % Number of the frequency bins for the given acquisition band numberoffrqbins = round(settings.acqsearchband * 2*5) + 1; % Generate all C/A codes and sample them according to the sampling freq: cacodestable = makecatable(settings); length(cacodestable); %--- Initialize arrays to speed up the code % Search results of all frequency bins and code shifts (for one satellite) results = zeros(numberoffrqbins, 20*samplesPerCode); % Carrier frequencies of the frequency bins frqbins = zeros(1, numberoffrqbins); %--- Initialize acqresults % Carrier frequencies of detected signals acqresults.carrfreq = zeros(1, 37); % C/A code phases of detected signals acqresults.codephase = zeros(1, 37); % Correlation peak ratios of the detected signals acqresults.peakmetric = zeros(1, 37); fprintf('('); % Perform search for all listed PRN numbers... for PRN = settings.acqsatellitelist % Correlate signals ====================================================== %--- Perform DFT of C/A code %Multiply C/A code on Neumann-Hoffman code (first 5 ms - otherwise too long wait time) %NH = "0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0"; cacodefreqdom = conj(fft([-1*cacodestable(prn, :) -1*caCodesTable(PRN, :)... -1*caCodesTable(PRN, :) -1*caCodesTable(PRN, :)... -1*caCodesTable(PRN, :)... zeros(1, 5*samplesPerCode)])); %--- Make the correlation for whole frequency band (for all freq. bins) for frqbinindex = 1:numberOfFrqBins %--- Generate carrier wave frequency grid (freqency step depends % on "settings.acqcohintegration") frqbins(frqbinindex) = settings.if -... (settings.acqsearchband/2) * (1000 / (2*5)) * (frqbinindex - 1); %--- Generate local sine and cosine sigcarr = exp(1i*frqbins(frqbinindex) * phasepoints); %--- "Remove carrier" from the signal and Convert the baseband % signal to frequency domain %pause; IQfreqDom1 = fft(sigcarr.* signal1); IQfreqDom2 = fft(sigcarr.* signal2); IQfreqDom3 = fft(sigcarr.* signal3); IQfreqDom4 = fft(sigcarr.* signal4);

37 %--- Multiplication in the frequency domain (correlation in time domain) convcodeiq1 = IQfreqDom1.* cacodefreqdom; convcodeiq2 = IQfreqDom2.* cacodefreqdom; convcodeiq3 = IQfreqDom3.* cacodefreqdom; convcodeiq4 = IQfreqDom4.* cacodefreqdom; %--- Perform inverse DFT and store correlation results acqres1 = abs(ifft(convcodeiq1)).^ 2; acqres2 = abs(ifft(convcodeiq2)).^ 2; acqres3 = abs(ifft(convcodeiq3)).^ 2; acqres4 = abs(ifft(convcodeiq4)).^ 2; %--- Check which msec had the greater power and save that, will %"blend" 1st and 2nd "settings.acqcohintegration" msec but will % correct data bit issues %/results(frqbinindex, :) = acqres1(1:samplespercode); %/results(frqbinindex, :) = acqres2(1:samplespercode); %/results(frqbinindex, :) = acqres3(1:samplespercode); %/results(frqbinindex, :) = acqres4(1:samplespercode); %pause; results(frqbinindex, :) = [acqres1(1:5*samplespercode)... acqres2(1:5*samplespercode)... acqres3(1:5*samplespercode)... acqres4(1:5*samplespercode)]; % if ( (max(acqres1) > max(acqres2)) &.. % (max(acqres1) > max(acqres3)) &.. % (max(acqres1) > max(acqres4))) % results(frqbinindex, :) = acqres1; % code_phase_corr = 0*samplesPerCode/4; % code_phase_slot = 1; % elseif ( (max(acqres2) > max(acqres1)) &.. % (max(acqres2) > max(acqres3)) &.. % (max(acqres2) > max(acqres4))) % results(frqbinindex, :) = acqres2; % code_phase_corr = 1*samplesPerCode/4; % code_phase_slot = 12; % elseif ( (max(acqres3) > max(acqres1)) &.. % (max(acqres3) > max(acqres2)) &.. % (max(acqres3) > max(acqres4))) % results(frqbinindex, :) = acqres3; % code_phase_corr = 2*samplesPerCode/4; % code_phase_slot = 3; % else % results(frqbinindex, :) = acqres4; % code_phase_corr = 3*samplesPerCode/4; % code_phase_slot = 4; % end end % frqbinindex = 1:numberOfFrqBins % Look for correlation peaks in the results ============================== % Find the highest peak and compare it to the second highest peak % The second peak is chosen not closer than 1 chip to the highest peak %--- Find the correlation peak and the carrier frequency [peaksize frequencybinindex] = max(max(results,[],2)); %--- Find code phase of the same correlation peak [peaksize codephase] = max(max(results));

38 %--- Find 1 chip wide CA code phase exclude range around the peak ---- samplespercodechip = round(settings.samplingfreq /... settings.acqresamplecoef /... settings.codefreqbasis); excluderangeindex1 = codephase - samplespercodechip; excluderangeindex2 = codephase + samplespercodechip; %--- Correct C/A code phase exclude range if the range includes array %boundaries if excluderangeindex1 < 2 codephaserange = excluderangeindex2 :... (samplespercode + excluderangeindex1); elseif excluderangeindex2 > samplespercode codephaserange = (excluderangeindex2 - samplespercode) :... excluderangeindex1; else codephaserange = [1:excludeRangeIndex1,... excluderangeindex2 : samplespercode]; end %--- Find the second highest correlation peak in the same freq. bin --- secondpeaksize = max(results(frequencybinindex, codephaserange)); %--- Store result acqresults.peakmetric(prn) = peaksize/secondpeaksize; % If the result is above threshold, then there is a signal... if (peaksize/secondpeaksize) > settings.acqthreshold %--- Indicate PRN number of the detected signal fprintf('%02d ', PRN); acqresults.codephase(prn) = (codephase-1) * settings.acqresamplecoef; acqresults.carrfreq(prn) =... settings.if -... (settings.acqsearchband/2) * (1000 / (2*5)) * (frequencybinindex - 1); else %--- No signal with this PRN fprintf('. '); end % if (peaksize/secondpeaksize) > settings.acqthreshold end % for PRN = satellitelist %=== Acquisition is over ================================================== fprintf(')\n');

39 3. Tracking code function [trackresults, channel]= tracking(fid, channel, settings) % Performs code and carrier tracking for all channels. % %[trackresults, channel] = tracking(fid, channel, settings) % % Inputs: % fid - file identifier of the signal record. % channel - PRN, carrier frequencies and code phases of all % satellites to be tracked (prepared by prerum.m from % acquisition results). % settings - receiver settings. % Outputs: % trackresults - tracking results (structure array). Contains % in-phase prompt outputs and absolute spreading % code's starting positions, together with other % observation data from the tracking loops. All are % saved every millisecond. % % % Initialize result structure ============================================ % Channel status trackresults.status = '-'; % No tracked signal, or lost lock % The absolute sample in the record of the C/A code start: trackresults.absolutesample = zeros(1, settings.mstoprocess); % Freq of the C/A code: trackresults.codefreq = ones(1, settings.mstoprocess).*inf; % Frequency of the tracked carrier wave: trackresults.carrfreq = ones(1, settings.mstoprocess).*inf; % Outputs from the correlators (In-phase): trackresults.i_p = zeros(1, settings.mstoprocess); trackresults.i_e = zeros(1, settings.mstoprocess); trackresults.i_l = zeros(1, settings.mstoprocess); % Outputs from the correlators (Quadrature-phase): trackresults.q_e = zeros(1, settings.mstoprocess); trackresults.q_p = zeros(1, settings.mstoprocess); trackresults.q_l = zeros(1, settings.mstoprocess); % Loop discriminators trackresults.dlldiscr trackresults.dlldiscrfilt trackresults.plldiscr trackresults.plldiscrfilt = ones(1, settings.mstoprocess).*inf; = ones(1, settings.mstoprocess).*inf; = ones(1, settings.mstoprocess).*inf; = ones(1, settings.mstoprocess).*inf; %--- Copy initial settings for all channels trackresults = repmat(trackresults, 1, settings.numberofchannels); % Initialize tracking variables ==========================================