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ION Southern California Section Meeting

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. Outline. Software GPS Receivers: Definitions

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ION Southern California Section Meeting

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  1. 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

  2. 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

  3. RF IC Application Platform Down- Converters (BPF, AMP, Mixers) ADC Processor Application Software ANT LNA RAM I/O I/O • Signal • Processor • - Acquisition • Tracking Data Processor - Demodulation - Positioning - Interface Power Supply Code/Carrier Generators Correlators ROM Software GPS Receivers: Definitions • Typical Architecture of GPS Receivers in Use Today Baseband IC/Microprocessor ~GHz ~MHz ~kHz ~Hz

  4. Application Platform Down- Converters (BPF, AMP, Mixers) ADC Processor Software for - Acquisition - Tracking - Demodulation - Positioning Application Software ANT LNA DMA RAM RAM I/O I/O I/O • Software for • Code/Carrier • Generation • - Correlation Power Supply ROM ROM Software GPS Receivers: Definitions • Software GPS Receivers: from IF samples to position fix, • all implemented in software on a general purpose computer General Purpose Processor RF IC Processor ~GHz ~Hz Several Hundreds ~ Tens MHz As close to RF as possible Total signal bandwidth Several RF channels, e.g., L1, L2, L5

  5. Software GPS Receivers: Definitions • Tools for Algorithms Evaluation • Hardware Receiver Simulator • Post-Processing of Recorded IF Samples • Real-Time Research/Commercial Receivers • Software-Configured Hardware Correlator - Configurable Code Generators & NCOs - Sequential Repeated at Very High Speed (>> fs) • Software-Implemented Correlators: - Time-Domain Sum of Products (XOR, I&D, LUT) - FFT-Implemented Correlation (Acquisition, Tracking) Historical Development of Software Receivers Software Defined Radio (SDR)

  6. 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, “Performance Evaluation of a Multi-frequency GPS/Galileo/SBAS Software Receiver,” ION-GNSS’07, Ft. Worth, TX, September 2007

  7. 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 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. 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

  9. 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

  10. Recent Developments & Trends ±Tc ±Tc BOC(s,c) ±Ts BPSK • 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 • Code-dependent • Code structure-dependent • Affected by effective bandwidth

  11. Recent Developments & Trends Uploaded Navigation Data Bits Atomic Clock Carrier Modulation Local Clock • GPS Signal’s Channel Impulse Response GPS Satellite A PRN Code Generation Power Amplification Transmit Antenna Transmit Shaping Filter ht(t) Signal & Data Processors Signal Digital Samples Receiver Front-end Receive Antenna User B Digital Receiver Receive Shaping Filter hr(t)

  12. Recent Developments & Trends Uploaded Navigation Data Bits Atomic Clock Carrier Modulation Local Clock • GPS Signal’s Channel Impulse Response GPS Satellite Propagation Channel A PRN Code Generation Power Amplification Transmit Antenna Ionosphere Transmit Shaping Filter ht(t) Propagation Channel Impulse Response hp(t) Troposphere Environment Direct Signal Signal & Data Processors Signal Digital Samples Receiver Front-end Receive Antenna User B Multipath Signals {ai, ti, i = 1, …, M} Digital Receiver Receive Shaping Filter hr(t)

  13. Recent Developments & Trends Uploaded Navigation Data Bits Atomic Clock Carrier Modulation Local Clock • GPS Signal’s Channel Impulse Response GPS Satellite Propagation Channel A PRN Code Generation Power Amplification Transmit Antenna Ionosphere Transmit Shaping Filter ht(t) Propagation Channel Impulse Response hp(t) Satellite Signal Channel Impulse Response h(t) = hr(t)*hp(t)*ht(t) Channel Transfer Function H(f) = F{h(t)} and h(t) = F-1{H(f)} (* Convolution, F Fourier Transform, F-1 Inverse Fourier Transform) Troposphere Environment Direct Signal Signal & Data Processors Signal Digital Samples Receiver Front-end Receive Antenna User B Multipath Signals {ai, ti, i = 1, …, M} Digital Receiver Receive Shaping Filter hr(t) C. Yang and M. Miller, “Novel GNSS Receiver Design Based On Satellite Signal Channel Transfer Function/Impulse Response,” Proc. of ION-GNSS’05, Long Beach, CA, Sept. 2005

  14. Recent Developments & Trends • GPS Signal’s Channel Impulse Response Ideal Dirac Delta Function (Flat Infinite Spectrum)

  15. Recent Developments & Trends • GPS Signal’s Channel Impulse Response Ideal Dirac Delta Function (Flat Infinite Spectrum) Ideal Correlation with Spectrum Limited to fs/2 Conventional Correlation Function Correlation with Spectrum Limited to feff ±Tc = 1/fc

  16. Recent Developments & Trends • GPS Signal’s Channel Impulse Response Ideal Dirac Delta Function (Flat Infinite Spectrum) Impulse Response (Generalized Correlation) Normalized Correlation with Spectrum Limited to fs/2 Normalized Correlation with Spectrum Limited to feff Ideal Correlation with Spectrum Limited to fs/2 Conventional Correlation Function Correlation with Spectrum Limited to feff ±Ts = 1/fs ±Teff = 1/feff ±Tc = 1/fc

  17. 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

  18. 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

  19. Recent Developments & Trends  GPS RF ADC Front-End Correlation Power D f IFFT Dt Delay-Doppler Map Code Complex Replica FFT Conjugate Sequences • Frequency-Domain Baseband Signal Processor Forward Transformation - Signal Spectrum FFT Shift for Doppler Removal Detection Inverse Transformation Forward Transformation - Replica

  20. Recent Developments & Trends  Narrowband Pseudo Quadrature Sampling Extended Buffer GPS RF Interference ADC Front-End Suppression Complex Correlation D Detection Full or f DFT for ms-Alignment Partial or Residual Data Bit Sync Pruning Doppler Interpolation IFFT Dt Delay-Doppler Map Code Complex Replica FFT Conjugate Sequences • Frequency-Domain Baseband Signal Processor Forward Transformation - Signal Spectrum Full/Zoom FFT Shift for Doppler Removal Carrier GPS Signal Doppler Parameters Parameter Extraction Inverse Transformation Forward Transformation - Replica

  21. Recent Developments & Trends / Narrowband Pseudo Quadrature Sampling Extended Buffer GPS RF Interference ADC Front-End Suppression Complex Correlation D Detection Full or f DFT for ms-Alignment Partial or Residual Data Bit Sync Pruning Doppler Interpolation IFFT Dt Delay-Doppler Map Code Complex Resampling Replica FFT Conjugate Sequences • Frequency-Domain Baseband Signal Processor Forward Transformation - Signal Spectrum Full/Zoom FFT Shift for Doppler Removal Carrier GPS Signal Doppler Parameters Parameter Extraction Inverse Transformation Code Phases Code Doppler Forward Transformation - Replica

  22. Recent Developments & Trends Multipath Mitigated Correlation Composite Signal s(t) Correlation Spectrum Signal Spectrum S(f)  FFT IFFT  Multipath Estimation  Replica Spectrum R(f) Replica r(t) Multipath Transfer Function FFT * Autocorrelation Spectrum • Frequency-Domain Baseband Signal Processor Parametric Signal Spectrum Correlation Spectrum Transfer Function Multipath Parameters Multipath Mitigation Non-Parametric

  23. Recent Developments & Trends s(t) S(f) Spectrum Filtering U Fourier Transform c(t) Delay-Doppler Map of Complex Generalized Correlations C(f) Inverse Fourier Transform Spectrum Filtering W R*(f) r(t) Fourier Transform Conjugate Spectrum Filtering V Generalized Frequency-Domain Correlator (GFDC) Frequency-Domain Baseband Signal Processor Code Replica Samples Buffer Incoming Signal Samples Buffer Peak Detection & Parameters Extraction • Generalized Frequency-Domain Correlator (GFDC)

  24. 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 • Spectrum Windowing/Filtering Conventional Correlation Impulse Response Phase-Only Correlation Symmetric Phase Only Square-Root Normalized Amplitude-Compensated Make One of Your Own … 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

  25. 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 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

  26. Recent Developments & Trends • Generalized Frequency-Domain Correlator (GFDC)  Symmetric Phase-Only Matched Filter (SPOMF) 3 Pairs of Curves: With and Without Multipath Signal + Noise + Multipath Signal + Noise ▪ Conventional Correlation  Conventional Correlation Signal + Noise + Multipath Signal + Noise ▪Impulse Response  Impulse Response (SCIR) ▪Symmetric Phase-Only Signal + Noise + Multipath Signal + Noise Infinite Bandwidth Fixed Relative Strength a = 0.2 Same Noise at Each Delay

  27. Recent Developments & Trends Triple-Band Antenna, RF Front-End & ADC Narrowband L1C-Code Narrowband L2C (CM & CL) Single Band Antenna, RF Front-End & ADC Spectrum Segmentation Dual-Band Antenna, RF Front-End & ADC Wideband P(Y)-Code Split-band M-Code Spectrum Filtering Spectrum Filtering Wideband L5 (I5 & Q5) • Frequency-Domain Baseband Signal Processor Narrowband L1 C/A-Code L1, L2 or L5 Full Spectrum per Band L1/L2 or L1/L5 50 Msps 24 MHz Spectrum Screening for Spike Excision L1, L2 Complex DFT/FFT 50,000 Complex DFT/FFT per 1 ms L1, L2 and L5 L5 Incoming Signal FFT Only Done Once But Used for All Codes for All Satellites!  Spectrum Segmentation = Ideal Bandpass Filtering

  28. Recent Developments & Trends Parameter N Parameter 1 Parameter 2 ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ • Block-Repeated Iterative Processing Block 2 Block 1 Block 3 Block M Time Block N Parallel Processing Sequential Processing Parameter 1 Parameter 2 Parameter N Parameter n+1 Parameter 1 Parameter N-n+1 Sequential Parallel Processing Parameter n Parameter 2n Parameter N • Multipath Mitigation • Near-Far Interference Cancellation • Iterative Approximation to Nonlinearity • Successive Removal of High Dynamics Parameter 1 Parameter 2 Block Repetitive Processing Parameter N

  29. 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

  30. Recent Developments & Trends Destructive Constructive Ideal Case (Orthogonal) y as as as y y Noise Cloud Non Orthogonal s s s aw w w aw w aw Weak Signal Weak Signal Cross-Correlation of Strong Signal (i.e., Projection) None of Strong Signal Projection (w/o Cross Correlation) Cross-Correlation of Strong Signal (i.e., Projection) Weak Signal Out of Noise • Strong-Weak Signal (Near-Far) Problem: Cause & Effect • - Masking of Weak Signals by Strong Signals • - Non-orthogonality (Cross-Correlation) between Codes s: Strong Signal (as) w: Weak Signal (aw) y: Received Signal

  31. Recent Developments & Trends • Strong-Weak Signal (Near-Far) Problem: Signal Models Amplitude Vector Number of Correlation Samples Unit Amplitude Matrix Strong Signals Weak Signals

  32. 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] • Signal Subspace Projection [Morton et al., 2007] • Unnormalized Oblique Projection [Behrens & Scharf, 1994; • Thomas et al., 2004] • Constrained Optimization for Adaptive Replica Equivalent

  33. Recent Developments & Trends • Successive Interference Cancellation (SIC) • - Signal Domain Iteration [Madhani et al., 2001]

  34. Recent Developments & Trends • Successive Interference Cancellation (SIC) • - Correlation Domain Iteration [Norman & Cahn, 2004]

  35. 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

  36. Recent Developments & Trends • Signal Subspace Projection [Morton et al.] Projection onto <S>: PS = S(STS)-1ST - Strong Signal Subspace: <S> = span{s1, s2, …, sM} NN - Recover Strong Signals via Subspace Projection: - Remove Strong Signals: - Detect Weak Signals: 1NmmN1 Projection onto Orthogonal Subspace Equivalent code replica

  37. 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

  38. 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:

  39. 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

  40. Recent Developments & Trends • Signal Subspace Projection [Morton et al.] Success Rate (%) Success Rate (%) Without Removal Success Rate (%) Without Removal Achieve 90% Success Rate

  41. 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

  42. Recent Developments & Trends • Multipath Error with “E-L” Code Error Discriminator p = Multipath Delay wrt Direct Path q = Bias in Delay Error Discriminator S = Correlator Spacing T = Chip Duration Ed, Pd, Ld = Direct Signal Correlation Er, Pr, Lr = Multipath Signal Correlation E = Early, P = Prompt, L = Late

  43. Recent Developments & Trends • Multipath Mitigation Methods at Correlator Narrow Correlator Double Delta Correlator: - Strobe Correlator - Pulse Aperture Correlator - Gated Correlator Multipath Elimination Technique (Slopes) E1/E2 Tracking Multipath Estimating Correlator (Parametric) High Resolution Vision Correlator Impulse Response    Number of correlators Correlator spacing Correlator location Correlator weighting  Improved Multipath Performance at the Cost of Increased Thermal Noise

  44. Recent Developments & Trends VVL VL L P E VE VVE Code Generator • Synthesize Code Error Discriminator (S-Curve Shaping) Incoming Signal R(Dt-4d) a-4 S* R(Dt-3d) a-3 S* R(Dt-2d) a-2 S* R(Dt-d) a-1 Optimal Code Error Discriminator S* As narrow as possible in tracking Local Code D(Dt) = kDt R(Dt) a0 S* R(Dt+d) a1 S* d R(Dt+2d) D(Dt) a2 S* R(Dt+3d) a3 S-Curve S* R(Dt+4d) a4 S* 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 Code Multipath Mitigation,” ION-GNSS’2005, Long Beach, CA

  45. Recent Developments & Trends • Synthesize Code Error Discriminator (S-Curve Shaping) = R a d Alternative Solution N -N = Dtj 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 Code Multipath Mitigation,” ION-GNSS’2005, Long Beach, CA

  46. 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 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

  47. 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

  48. Software Communications Architecture (SCA) Applications Core Framework (CF) Operating Environment (OE) Non-CORBA Commercial Off-the-Shelf (COTS) Security Components Non-CORBA Non-CORBA Modem I/O Components Components Physical API RF Link, Network Security Modem I/O Modem Security Link, Network I/O Security Adapter Components Components Components Components Components Adapter Adapter Adapter MAC API LLC/Network API Security API LLC/Network API I/O API (“Logical Software Bus” via CORBA) Core Framework IDL CF CF CORBA ORB & CORBA ORB & Services & Services & Services Services Applications (Middleware) Applications (Middleware) Operating System Network Stacks & Serial Interface Services Network Stacks & Serial Interface Services Operating System Board Support Package (Bus Layer) Board Support Package (Bus Layer) Red Hardware Bus Black Hardware Bus  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

  49. 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

  50. 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

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