Document Sample

ION Southern California Section Meeting Software GPS Receivers: Some Recent Developments & Trends Chun Yang Sigtem Technology, Inc. San Mateo, CA (650) 312-1132 chunyang@sigtem.com June 25, 2008 1 Outline • Software GPS Receivers: Definitions • Example of a State of the Art Implementation • Recent Developments & Trends - GPS Signal’s Channel Impulse Response - Frequency-Domain Baseband Processor - Online Adaptive Code Replica Synthesis • Standardization 2 Software GPS Receivers: Definitions • Typical Architecture of GPS Receivers in Use Today RF IC Baseband IC/Microprocessor Application Platform ANT Down- Processor ADC Correlators Signal Data Processor LNA Converters (BPF, AMP, Processor - Demodulation Application - Positioning I/O I/O Mixers) Code/Carrier - Acquisition Software Generators - Tracking - Interface Power Supply RAM ROM ~GHz ~MHz ~kHz ~Hz 3 Software GPS Receivers: Definitions • Software GPS Receivers: from IF samples to position fix, all implemented in software on a general purpose computer RF IC General Purpose Processor Application Platform ANT Down- Processor Processor ADC DMA LNA Converters (BPF, AMP, Software for Software for I/O I/O Application I/O Mixers) - Acquisition - Code/Carrier Software - Tracking Power Generation - Demodulation Supply - Correlation - Positioning RAM ROM ~GHz RAM ROM ~Hz Several As close to RF Hundreds Total signal bandwidth as possible ~ Tens MHz Several RF channels, e.g., L1, L2, L5 4 Software GPS Receivers: Definitions Tools for Algorithms Evaluation Historical Hardware Receiver Simulator Development Post-Processing of Recorded IF Samples of Software Real-Time Research/Commercial Receivers Receivers Software-Configured Hardware Correlator Software Defined - Configurable Code Generators & NCOs Radio - Sequential Repeated at Very High Speed (>> fs) (SDR) Software-Implemented Correlators: - Time-Domain Sum of Products (XOR, I&D, LUT) - FFT-Implemented Correlation (Acquisition, Tracking) 5 State of the Art SW GNSS Receiver Example • NavX-NSR by IfEN & University FAF Munich • 1st Interactive GPS/Galileo Software Receiver - Triple-Frequency RF Front-End with USB (312.5 Mbps) - 30% of CPU on 2 Intel Xeon 5140 Processors Tracking 18 Satellites - 85% Computation Time for Correlation - GUI for Results and Runtime Control of Channel Configuration, Signal/Code Structure, Processing Algorithms, & Receiver Parameters M. Anghileri, T. Pany, D.S. Güixens, J.H. Won, A.S. Ayaz, C. Stöber, I. Krämer, D. Dötterböck, G.W. Hein, and B. Eissfeller, 6 “Performance Evaluation of a Multi-frequency GPS/Galileo/SBAS Software Receiver,” ION-GNSS’07, Ft. Worth, TX, September 2007 State of the Art SW GNSS Receiver Example Search Strategy: - All resources used to acquire and track a satellite - Extract information from the signal to correct large errors of the PC clock - With timing, calculate approximate satellite position from almanac or ephemeris Acquisition: - FFT-implemented correlation - Two levels of acquisition (high-power first) with interference cancellation - Coherent and non-coherent integration - Time and Doppler search space reduced for weak signals and re-acquisition Tracking: - Mixed FLL and PLL for carrier, rate-aided DLL for code - Frequency error discriminator: mixture of 2-quadrant and 4-quadrant atan2’s Optimized reference waveform (S-curve shaping technique): - Weighted combination of several replicas to achieve a pre-specified S-curve Bit synchronization: - Kalman filter tracking of carrier phase, Doppler, and Doppler rate errors - MLE of bit edge positions - Forward error corrections & Viterbi decoder Navigation Solution: - Single-epoch least squares solution - Kalman navigation filter optimized for car navigation - Pseudoranges, carrier phase and Doppler as well as height and clock fixing 7 M. Anghileri, T. Pany, D.S. Güixens, J.H. Won, A.S. Ayaz, C. Stöber, I. Krämer, D. Dötterböck, G.W. Hein, and B. Eissfeller, “Performance Evaluation of a Multi-frequency GPS/Galileo/SBAS Software Receiver,” ION-GNSS’07, Ft. Worth, TX, September 2007 State of the Art SW GNSS Receiver Example Programming Features: - An object-oriented programming approach with C++ - Classes grouped into modules with well-defined input and output data streams - UML diagram design before implementation - Maximum reuse of source codes - Common algorithms and data structures are implemented as base class (abstract class) - Particular features are then specified in derived classes (inheritance) - Codes optimized with assembler instructions - Multi-threading for better real-time capability Performance: - Code measurement accuracy: better than 30 cm - Carrier phase measurement accuracy: better than 1 mm - In-door positioning capability: FLL operates on signals down to 10 dB-Hz Need a Software Receiver Standard? M. Anghileri, T. Pany, D.S. Güixens, J.H. Won, A.S. Ayaz, C. Stöber, I. Krämer, D. Dötterböck, G.W. Hein, and B. Eissfeller, “Performance Evaluation of a Multi-frequency GPS/Galileo/SBAS Software Receiver,” ION-GNSS’07, Ft. Worth, TX, September 2007 8 Outline • Software GPS Receivers: Definitions • Example of a State of the Art Implementation • Recent Developments & Trends - GPS Signal’s Channel Impulse Response - Frequency-Domain Baseband Processor - Online Adaptive Code Replica Synthesis • Standardization 9 Recent Developments & Trends • GPS Signal’s Channel Impulse Response vs. Correlation • Correlation: Vital Role in DS-SS CDMA Receivers - Despread (processing gain) for signal detection - Identify which satellite the signal originated from - Provide timing (code/carrier phase) to construct measurements - Enable data demodulation for navigation message - Performance-limiting mix-in point for interference, multipath, etc. - Data compression from MHz to kHz (intensive) - Its implementation distinguishes HW vs. SW receivers ±Tc Code-dependent ±Tc Code structure-dependent Affected by effective bandwidth BPSK ±Ts BOC(s,c) 10 Recent Developments & Trends • GPS Signal’s Channel Impulse Response Uploaded GPS Satellite Navigation Data Bits A Atomic PRN Code Carrier Power Transmit Clock Generation Modulation Amplification Antenna Transmit Shaping Filter h t(t) Local Clock Signal Signal Receiver Receive User & Data Digital Front-end Antenna Processors B Samples Digital Receiver Receive Shaping Filter h r(t) 11 Recent Developments & Trends • GPS Signal’s Channel Impulse Response Uploaded GPS Satellite Navigation Data Bits Propagation Channel A Atomic PRN Code Carrier Power Transmit Clock Generation Modulation Amplification Antenna Ionosphere Transmit Shaping Filter h t(t) Propagation Channel Troposphere Impulse Response hp(t) Local Clock Environment Direct Signal Signal Signal Receiver Receive User & Data Digital Front-end Antenna Processors B Samples Multipath Signals {ai, ti, i = 1, …, M} Digital Receiver Receive Shaping Filter h r(t) 12 Recent Developments & Trends • GPS Signal’s Channel Impulse Response Uploaded GPS Satellite Navigation Data Bits Propagation Channel A Atomic PRN Code Carrier Power Transmit Clock Generation Modulation Amplification Antenna Ionosphere Transmit Shaping Filter h t(t) Propagation Satellite Signal Channel Impulse Response h(t) = hr(t)*hp(t)*ht(t) Channel Channel Transfer Function H(f) = F{h(t)} and h(t) = F -1{H(f)} Troposphere Impulse (* Convolution, F Fourier Transform, F -1 Inverse Fourier Transform) Response hp(t) Local Clock Environment Direct Signal Signal Signal Receiver Receive User & Data Digital Front-end Antenna Processors B Samples Multipath Signals {ai, ti, i = 1, …, M} Digital Receiver Receive Shaping Filter h r(t) C. Yang and M. Miller, “Novel GNSS Receiver Design Based On Satellite Signal Channel Transfer Function/Impulse Response,” 13 Proc. of ION-GNSS’05, Long Beach, CA, Sept. 2005 Recent Developments & Trends • GPS Signal’s Channel Impulse Response Dirac Delta Function (Flat Infinite Spectrum) Ideal 14 Recent Developments & Trends • GPS Signal’s Channel Impulse Response Dirac Delta Function (Flat Infinite Spectrum) Ideal Ideal Correlation with Spectrum Limited to f s/2 Conventional Correlation Correlation with Spectrum Function Limited to feff ±Tc = 1/f c 15 Recent Developments & Trends • GPS Signal’s Channel Impulse Response Dirac Delta Function (Flat Infinite Spectrum) Ideal Normalized Correlation Impulse with Spectrum Limited to f s/2 Response Normalized Correlation (Generalized with Spectrum Limited to f eff Correlation) Ideal Correlation with Spectrum Limited to f s/2 Conventional Correlation Correlation with Spectrum Function Limited to feff ±Ts = 1/f s ±Teff = 1/f eff ±Tc = 1/f c 16 Recent Developments & Trends • What is a GPS signal channel impulse response? - From the output of a signal generator at satellite to the output of ADC at receiver - Encompass satellite, propagation, receiving environment, and receiver front-end • What are its benefits vs. conventional correlation? - Better timing accuracy, less sensitive to multipath, same operation for all codes • How to obtain a channel impulse response? - System identification (parametric, non-parametric, richness of excitation) - Inverse filter (phase-only and variants) - Wiener filter • When to outperform (what are limiting factors)? - Equivalent bandwidth of signal, propagation, transmitter, and receiver - Sampling rate - Signal to noise ratio (SNR): at input vs. processing loss - Computational loading 17 Outline • Software GPS Receivers: Definitions • Example of a State of the Art Implementation • Recent Developments & Trends - GPS Signal’s Channel Impulse Response - Frequency-Domain Baseband Processor - Online Adaptive Code Replica Synthesis • Standardization 18 Recent Developments & Trends • Frequency-Domain Baseband Signal Processor Forward Transformation - Signal Spectrum GPS RF Shift for ADC FFT Front-End Doppler Removal Correlation Power Detection Df IFFT Inverse Dt Transformation Delay-Doppler Map Code Complex Replica FFT Conjugate Sequences 19 Forward Transformation - Replica Recent Developments & Trends • Frequency-Domain Baseband Signal Processor Forward Transformation - Signal Pseudo Spectrum Full/Zoom Narrowband GPS RF Extended Quadrature Shift for ADC FFT Interference Front-End Buffer Sampling Doppler Suppression Removal GPS Signal Carrier Parameters Doppler Complex Correlation Detection Df Full or Parameter DFT for ms-Alignment Partial or Extraction Residual Data Bit Sync Pruning Doppler Interpolation IFFT Inverse Dt Transformation Delay-Doppler Map Code Complex Replica FFT Conjugate Sequences 20 Forward Transformation - Replica Recent Developments & Trends • Frequency-Domain Baseband Signal Processor Forward Transformation - Signal Pseudo Spectrum Full/Zoom Narrowband GPS RF Extended Quadrature Shift for ADC FFT Interference Front-End Buffer Sampling Doppler Suppression Removal GPS Signal Carrier Parameters Doppler Complex Correlation Detection Df Full or Parameter DFT for ms-Alignment Partial or / Extraction Residual Data Bit Sync Pruning Doppler Interpolation IFFT Inverse Dt Transformation Delay-Doppler Map Code Phases Code Doppler Code Complex Replica Resampling FFT Conjugate Sequences 21 Forward Transformation - Replica Recent Developments & Trends • Frequency-Domain Baseband Signal Processor Multipath Mitigated Composite Signal Correlation Correlation Signal s(t) Spectrum S(f) Spectrum FFT IFFT Multipath Estimation Replica Replica Multipath r(t) Spectrum R(f) Transfer FFT * Function Autocorrelation Spectrum Parametric Signal Correlation Transfer Multipath Multipath Spectrum Spectrum Function Parameters Mitigation Non-Parametric 22 Recent Developments & Trends • Generalized Frequency-Domain Correlator (GFDC) s(t) S(f) Incoming Signal Fourier Spectrum c(t) Samples Buffer Transform Filtering U C(f) Delay-Doppler Inverse Map of Peak Detection Spectrum Complex & Parameters Fourier Filtering W Generalized Extraction r(t) R*(f) Transform Correlations Code Replica Fourier Spectrum Samples Buffer Transform Filtering V Conjugate Generalized Frequency-Domain Correlator (GFDC) Frequency-Domain Baseband Signal Processor 23 Recent Developments & Trends Two Types of Filtering: Applied to Individual Frequency Bins Involving the Entire Spectrum Examples of Filtering: • Spectrum Excision of Narrowband Interference • Spectral Filtering to Reduce Additive Noise • Spectrum Segmentation of Multiple Codes • Spectrum Translation for Residual Doppler Removal with Feedback Conventional Correlation Impulse Response • Spectrum Windowing/Filtering Phase-Only Correlation Symmetric Phase Only Square-Root Normalized Amplitude-Compensated Make One of Your Own …24 C. Yang, M. Miller, and T. Nguyen, “Symmetric Phase-Only Matched Filter (SPOMF) for Frequency-Domain Software GPS Receivers,” ION Journal: Navigation, Vol. 54, No. 1, Spring 2007 Recent Developments & Trends • Phase-Only Correlation BPSK BOC Adaptive Waveforms: Correlation in Acquisition Phase-Only in Tracking C/A-Code to Achieve Performance of P-Code In Accuracy and Multipath Same Operation for Both BPSK- and BOC-Codes 25 C. Yang, M. Miller, and T. Nguyen, “Symmetric Phase-Only Matched Filter (SPOMF) for Frequency-Domain Software GPS Receivers,” ION Journal: Navigation, Vol. 54, No. 1, Spring 2007 Recent Developments & Trends • Generalized Frequency-Domain Correlator (GFDC) Symmetric Phase-Only 3 Pairs of Curves: With and Without Multipath Matched Filter (SPOMF) ▪ Conventional Correlation Signal + Noise + Multipath Conventional Correlation Signal + Noise ▪ Impulse Response Signal + Noise + Multipath Impulse Response (SCIR) Signal + Noise ▪ Symmetric Phase-Only Signal + Noise + Multipath Signal + Noise Infinite Bandwidth 26 Fixed Relative Strength a = 0.2 Same Noise at Each Delay Recent Developments & Trends • Frequency-Domain Baseband Signal Processor Narrowband L1 C/A-Code L1, L2 or L5 Full Spectrum Single Band Antenna, Spectrum Narrowband per Band RF Front-End & ADC Segmentation L1C-Code Narrowband L1/L2 or L1/L5 50 Msps 24 MHz Spectrum L2C (CM & CL) Complex L1, L2 Dual-Band Antenna, Screening RF Front-End & ADC DFT/FFT for Spike 50,000 Excision Wideband Complex P(Y)-Code Spectrum DFT/FFT Filtering per 1 ms Triple-Band Antenna, Split-band RF Front-End & ADC M-Code L1, L2 and L5 L5 Spectrum Wideband Incoming Signal FFT Only Done Once Filtering L5 (I5 & Q5) But Used for All Codes for All Satellites! Spectrum Segmentation = Ideal Bandpass Filtering 27 Recent Developments & Trends • Block-Repeated Iterative Processing Block 1 Block 2 Block 3 ▪ ▪ ▪ Block M ▪ ▪ ▪ Block N Time Parameter 1 Parameter 2 Parallel Processing ▪ ▪ ▪ Parameter N Sequential Processing Parameter 1 Parameter 2 ▪ ▪ ▪ ▪ ▪ ▪ Parameter N Sequential Parameter 1 Parameter n+1 ▪ ▪ ▪ Parameter N-n+1 Parallel ▪ ▪ ▪ ▪ ▪ ▪ Processing Parameter n Parameter 2n ▪ ▪ ▪ Parameter N • Multipath Mitigation Parameter 1 Parameter 2 Block ▪ • Near-Far Interference Cancellation Repetitive ▪ Processing ▪ • Iterative Approximation to Nonlinearity Parameter N 28 • Successive Removal of High Dynamics Outline • Software GPS Receivers: Definitions • Example of a State of the Art Implementation • Recent Developments & Trends - GPS Signal’s Channel Impulse Response - Frequency-Domain Baseband Processor - Online Adaptive Code Replica Synthesis Strong-Weak (Near-Far) Problem S-Curve-Shaping • Standardization 29 Recent Developments & Trends • Strong-Weak Signal (Near-Far) Problem: Cause & Effect - Masking of Weak Signals by Strong Signals - Non-orthogonality (Cross-Correlation) between Codes Ideal Case (Orthogonal) Constructive Destructive as y as y as y s: Strong Noise Cloud Non Signal (as) Orthogonal w: Weak Signal (aw) s s s y: Received Signal aw w aw w aw w Weak Signal Weak Signal None of Strong Signal Cross-Correlation Cross-Correlation Projection (w/o Weak Signal of Strong Signal of Strong Signal Cross Correlation) Out of Noise (i.e., Projection) (i.e., Projection) 30 Recent Developments & Trends • Strong-Weak Signal (Near-Far) Problem: Signal Models Amplitude Vector Unit Amplitude Matrix Number of Correlation Samples Strong Signals Weak Signals 31 Recent Developments & Trends • Strong-Weak Signal (Near-Far) Problem: Removal • Cancellation: - Signal Domain [Madhani et al., 2001] - Correlation Domain [Norman & Cahn, 2004] •Adaptive Orthogonalization with Constraints [Glennon & Dempster, 2007] Equivalent • Signal Subspace Projection [Morton et al., 2007] • Unnormalized Oblique Projection [Behrens & Scharf, 1994; Thomas et al., 2004] Constrained Optimization for Adaptive Replica 32 Recent Developments & Trends • Successive Interference Cancellation (SIC) - Signal Domain Iteration [Madhani et al., 2001] 33 Recent Developments & Trends • Successive Interference Cancellation (SIC) - Correlation Domain Iteration [Norman & Cahn, 2004] 34 Recent Developments & Trends • Adaptive Orthogonalization with Constraints [Glennon & Dempster] C/A-Code: - Max correlation = 1023 - Max cross correlations = -63 and +65, each @ 12.5% (-24 dB) - Typical cross correlation = -1 @ 75% (-60 dB) Cross-correlation due to imbalance of 64 out of 1023 chips Idea: rebalance the code via modifying 32 chips Procedure: - Calculate the total cross correlation (cc) between 2 sequences - Get indices of chips: sign of chip cc = sign of sequence cc - Sign-reverse some selected indices to eliminate cc Complexity: multiple strong signals, data bit, residual Doppler 35 Recent Developments & Trends • Signal Subspace Projection [Morton et al.] Projection onto <S>: - Strong Signal Subspace: <S> = span{s1, s2, …, sM} PS = S(STS)-1ST N N - Recover Strong Signals via Subspace Projection: - Remove Strong Signals: - Detect Weak Signals: 1N mm N1 Projection onto Orthogonal Subspace Equivalent code replica 36 Recent Developments & Trends • Constrained Optimization for Adaptive Replica - Constraints for Adaptive Code Replica : - Correlation with Synthesized Code: To Minimize - Constrained Optimization: Subject to - Solution: Similar to Subspace Projection with R = diagonal “Optimal” – noise minimized 37 Recent Developments & Trends • SINR Maximization for Adaptive Replica - Correlation with Synthesized Code to Find : CC between weak signals ignored Signal Noise + Interference - Optimality: Signal to Interference plus Noise Ratio - Constrained Optimization: Subject to - Solution: 38 Recent Developments & Trends • MSE Minimization for Adaptive Replica [Lacatus et al., 2007] - Signal already synchronized, to improve its reception quality - Optimality: Mean square error (MSE) minimization - Constrained Optimization: Subject to - Solution: - Complexity: R, p 39 Recent Developments & Trends • Signal Subspace Projection [Morton et al.] Success Rate (%) Success Rate (%) Without Removal Success Rate (%) Without Removal Achieve 90% Success Rate 40 Outline • Software GPS Receivers: Definitions • Example of a State of the Art Implementation • Recent Developments & Trends - GPS Signal’s Channel Impulse Response - Frequency-Domain Baseband Processor - Online Adaptive Code Replica Synthesis Strong-Weak (Near-Far) Problem S-Curve-Shaping • Standardization 41 Recent Developments & Trends • Multipath Error with “E-L” Code Error Discriminator S = Correlator Spacing p = Multipath Delay wrt Direct Path T = Chip Duration q = Bias in Delay Error Discriminator E = Early, P = Prompt, L = Late Ed , Pd , Ld = Direct Signal Correlation Er, Pr, Lr = Multipath Signal Correlation 42 Recent Developments & Trends • Multipath Mitigation Methods at Correlator Narrow Correlator Double Delta Correlator: - Strobe Correlator Number of correlators - Pulse Aperture Correlator Correlator spacing - Gated Correlator Correlator location Multipath Elimination Technique (Slopes) Correlator weighting E1/E2 Tracking Multipath Estimating Correlator (Parametric) High Resolution Vision Correlator Improved Multipath Performance at the Cost of Impulse Response Increased Thermal Noise 43 Recent Developments & Trends • Synthesize Code Error Discriminator (S-Curve Shaping) Incoming Signal R(Dt-4d) S* a-4 R(Dt-3d) VVL S* a-3 R(Dt-2d) VL S* a-2 R(Dt-d) Local Code L S* a-1 Optimal D(Dt) = kDt As narrow R(Dt) P S* a0 Code Error as possible R(Dt+d) E S* a1 Discriminator in tracking d R(Dt+2d) D(Dt) VE S* a2 R(Dt+3d) VVE S* a3 S-Curve R(Dt+4d) S* a4 Code Generator Dt As wide as possible in acquisition Operating Interval (±1 chips) T. Pany, M. Isigler, & B. Eissfeller, “S-Curve Shaping: A New Method for Optimum Discriminator Based 44 Code Multipath Mitigation,” ION-GNSS’2005, Long Beach, CA Recent Developments & Trends • Synthesize Code Error Discriminator (S-Curve Shaping) d = R a N = Alternative Solution Dtj -N Convolution of ai and R(id) -Ld 0 Ld id T. Pany, M. Isigler, & B. Eissfeller, “S-Curve Shaping: A New Method for Optimum Discriminator Based 45 Code Multipath Mitigation,” ION-GNSS’2005, Long Beach, CA Recent Developments & Trends • Synthesize Code Error Discriminator (S-Curve Shaping) Infinite 8 MHz Infinite 8 MHz Linear Region: 0.05 0.2 0.05 0.2 Fit Range: 1.5 2 1.5 2 Resolution: 0.05 0.2 0.05 0.2 Offset: 0 0.02 0.002 0.05 46 T. Pany, M. Isigler, & B. Eissfeller, “S-Curve Shaping: A New Method for Optimum Discriminator Based Code Multipath Mitigation,” ION-GNSS’2005, Long Beach, CA Outline • Software GPS Receivers: Definitions • Example of a State of the Art Implementation • Recent Developments & Trends - GPS Signal’s Channel Impulse Response - Frequency-Domain Baseband Processor - Online Adaptive Code Replica Synthesis • Standardization 47 Software Communications Architecture (SCA) SCA is Standards for Software Defined Radio (SDR) by JTRS - H/W & S/W specifications - Open architecture framework: how elements of hardware and software operate - Structure and operation: load waveforms, run applications, and networking to an integrated system Applications Core Framework (CF) Operating Environment (OE) Commercial Off-the-Shelf (COTS) Non-CORBA Non-CORBA Non-CORBA Modem Security I/O Components Components Components Physical RF API Modem Modem Link, Network Security Security Security Link, Network I/O I/O Components Adapter Components Adapter Components Adapter Components Adapter Components MAC API LLC/Network API Security API LLC/Network API I/O API Core Framework IDL (“Logical Software Bus” via CORBA) CORBA ORB & CF CORBA ORB & CF Services Services & Services Services & (Middleware) Applications (Middleware) Applications Operating System Operating System Network Stacks & Serial Interface Services Network Stacks & Serial Interface Services Board Support Package (Bus Layer) Board Support Package (Bus Layer) Black Hardware Bus Red Hardware Bus 48 A Software GPS Receiver Standard? Without Software GPS Receiver Standard - Hardware/software not totally compatible - A stand-alone software GPS receiver per manufacturer, proprietary - Result exchanges using common data format e.g. RINEX (a standard?) - A user has to stick with a manufacturer’s or buys from another With a Software GPS Receiver Standard - Specified to hardware/software functionality components similar to SCA for SDR - we can market a full software receiver, best software components for specific functionalities, common utilities, application specific software components, development tools, … - A user (government buyer) can select and assemble (plug and play) per needs New Business Models: Innovative Small Developers Can Play - Standard compliant platform vendors - Software development tools vendors - Baseband signal/data processors vendors - Applications-specific software vendors Industry-Wide Consortium for Standard Maintenance 49 Summary • Software GPS Receivers: Definitions • Example of a State of the Art Implementation • Recent Developments & Trends - GPS Signal’s Channel Impulse Response - Frequency-Domain Baseband Processor - Online Adaptive Code Replica Synthesis - Semi-Coherent Integration • Standardization 50 Thank you for your attention. Questions? 51 Questions – Enough Throughput for SW RX? • Xeon 5140 Processors - Clock rate of 2.33 GHz and 4 instructions executed per clock tick - 64-bit bus vs. 4-bit samples: 16 samples per transfer from ADC to CPU • Required Throughputs - Sampling rate = 40.96 MHz, Transfer rate = 40.96 MHz/16 = 2.56 MHz - Number of satellites = 18, Number of correlators = 4 (P, E-L for I & Q) - Required data throughput = 18 4 40.96 = 2949.12 MHz • Performance of NavX Implementation - 8 + 8 correlations per 2.5 to 4 clocks (More efficient with more satellite) - 6.4 to 4 correlations per clock, 3.2 to 2 correlations per processor per clock - CPU throughput: Max: 2 Xeon @ 2.33 GHz 3.2 correlations per clock = 10857.8 MHz Min: 2 Xeon @ 2.33 GHz 2 correlations per clock = 9320 MHz - Data throughput / CPU throughput = 2949.12/10088.9 = 29% ~ Claimed 30% - Cannot do multipath mitigation for L2CL (pre-compute double-delta replica) 52 Questions – Frequency-Domain Tracking? • Acquisition - Correlation at (code, frequency): N complex multiplications + N-1 complex additions - Sequential correlations: NcNfN = NfN2 complex multiplications - FFT-implemented correlations: NfNlog2N N/log2N ~ 186, 341 Times Less • Tracking for N = 2048, 4096 - Correlators: 3(N+N)M = 6NM, M = Number of codes - FFT: Nlog2N + 3NM + 5NM = (log2N + 8)NM ~ (19, 20)NM 3.5 Times More • Trade-offs - With a dedicated FFT processor, the computation is about the same - Except for different code replicas, exactly the same for BPSK & BOC - Blurred line between search & tracking: acquire, reacquire, coverage - Narrowband interference suppression - Signal channel transfer function/impulse response - Joint error discriminator & joint tracking loop across signals per satellite - Snapshot of 2 ms of data: delay and Doppler for all codes 53 Recent Developments & Trends • Semi-Coherent Integration Signal movement during integration Area covered Search in Time & Frequency: Search point Area of coverage 1/2Ti= 500 Hz Long Integration Interval: Df Unknown data bits Changes in frequency Search Point ½ Tc ½ ms Dt Correlator IF Samples zn = sn + wn Post-Correlation Despreading Integration Integration with @ 1 kHz {zn, n = 0, 1, …, N-1} Code Replica Search Director Carrier Replica 54 Recent Developments & Trends • Semi-Coherent Integration z = [z0, z1, …, zN-1]T N -1 1 - Ideal Coherent: lCI ( z ) = Re{ zn sn} * sn Known Perfectly n =0 Data Bits & Changes 2 - Practical Coherent with FFT: lCI _ FFT ( z ) = max{| FFT{z} |} in Doppler N -1 3 - Non-Coherent: lNCI ( z ) = zn zn * Squaring Removes Data Bits & Residual Doppler n=0 But Also Squares Noise & Loses Info bt & Df N -1 4 - Semi-Coherent for First Lag: l SCI ( z ) = z n z n-1 * Between Coherent & n=1 Non-coherent N/2 N 2 5 - Semi-Coherent up to First N/2 Lags: lSCI _ N / 2 ( z ) = * zn zn - k k =1 n = k +1 6 - Semi-Coherent for First Lag with FFT: l SCI _ FFT ( z ) = max{| FFT{diag ( z 1:N -1 ) z 0:N -2 } |} * 55 Recent Developments & Trends • Semi-Coherent Integration: Intra Block Products nth Block (over 1 Data Bit), 20 ms Ts N = 1000 for Ts = 1 ms i= 1 2 3 …… 8 9 10 11 …… 20 ½ ½ K blocks with M samples 1½ 1½ t – t/2 t – t/2 (e.g., M = 20, K = 50) 9½ t 9½ N = KM t Center of block Offset from the center Centered Autocorrelation Between Two Samples with Delay t Data bit sign is squared out Bilinear in t and t , thus allowing FFT Chirping rate a FFT over t , peak at f0+2a t, linear in t Bit Sync FFT over t, peak at 2at , linear in t Not Bit Sign C. Yang, M. Miller, T. Nguyen, and E. Blasch, “Wigner-Hough/Radon Transform for GPS Post-Correlation Integration,” ION-GNSS’07, Ft. Worth, TX, Sept. 2007 56 Recent Developments & Trends • Semi-Coherent Integration: Inter Block Products Delay t = MTs yk+2 = [x(k+2)i, i = 1, 2, …, M] k = 1, …, K: Block Index 12 …… M i = 1, …, M: Sample Index 12 …… M t = MTs: Delay between Blocks Ts = 1 ms, M = 20, K = 50 yk = [xki, i = 1, 2, …, M] Block k+1 Block k Block k+2 N = KM = 1000 (1 s) yk+1 = [x(k+1)i, i = 1, 2, …, M] Obtain Two Blocks of Complex Correlations: Construct (K-1)×M Matrix of Inter-Block Conjugate Products: 12 …… M Linear in k and i, thus allowing FFT Differential 2×1 1 FFT over k, peak at 2 at for each i Bit Sequence Z 3×2 … 2 … FFT of complex peaks over i 57 K×K-1 K-1 Recent Developments & Trends Block 1 Block 2 Block 3 MM 3M True Bit ++ + 1 2 3 4 …… 12 M 3M1 Transition 2M 2M+ 1 y1 y2 Twenty Sequences y3 of Delayed Blocks for yb Summation Aligned Delayed yM Blocks Joint Bit Sync, Sign & a Estimation: Detection with 3D Search Differential bit sequence Peak bin = l ~ a (Acceleration) Bit transition (sync) C. Yang, T. Nguyen, E. Blasch, and M. Miller, “Post-Correlation Semi-Coherent Integration for Weak 58 & High Dynamic GPS Signal Acquisition,” IEEE PLANS/ION-AM’08, Monterey, CA, May 2008 Recent Developments & Trends • Semi-Coherent Integration Pd vs. SNR for N = 100 (b = 37.45 Hz/s) Inter-Block Products C. Yang, M. Miller, T. Nguyen, and E. Blasch, “Comparative Study of Coherent, Non-Coherent, and Semi-Coherent Integration Schemes for GNSS Receivers,” Proc. of ION-AM’07, Boston, MA, April 2007. 59

DOCUMENT INFO

Shared By:

Categories:

Tags:
search engine, PDF Search, files search, Microsoft Powerpoint, PPT Files, compressive strength, GeV c, ASTM C, BS 1881, Microsoft Word

Stats:

views: | 11 |

posted: | 4/19/2011 |

language: | English |

pages: | 59 |

OTHER DOCS BY pengtt

Docstoc is the premier online destination to start and grow small businesses. It hosts the best quality and widest selection of professional documents (over 20 million) and resources including expert videos, articles and productivity tools to make every small business better.

Search or Browse for any specific document or resource you need for your business. Or explore our curated resources for Starting a Business, Growing a Business or for Professional Development.

Feel free to Contact Us with any questions you might have.