Bouncing off Walls and Trees: Multipath Channel Modeling for Satellite Navigation from the Samples Point of View F. M. Schubert German Aerospace Center (DLR) Institute for Communications and Navigation
TUM Navigation Colloquium 2 GNSS Channel Modeling and its Application in Simulation ESA Networking/Partnering Initiative (NPI) Partner institutions ESA s Networking and Partnering Initiative connects ESA to universities through PhD exchange Partner institutions German Aerospace Center (DLR) Institute for Communications and Navigation European Space Agency (ESA/ESTEC/TEC-EEP) European Space Research and Technology Center Aalborg University Navigation and Communications Section
TUM Navigation Colloquium 4 GNSS Channel Modeling and its Application in Simulation GPS C/A code correlation function Satellites send spreading codes Receiver correlates rx signal with locally generated code replica Correlation function R(τ) = 1 T c Tc 0 c(t)x(t t sp /2 τ)dt Code 1 01 C/A code, Prompt 3 2 C/A code ACF, chip spacing 1 early late multipath contribution (t = 0.4) sum Code 1 01 Early Correlation 1 0 Code Late 1 01 0 2 4 6 8 10 Time [µs] 1 2 2 1 0 1 2 Time delay [chips]
TUM Navigation Colloquium 5 GNSS Channel Modeling and its Application in Simulation GPS Receiver Tracking Loop Structure
TUM Navigation Colloquium 6 GNSS Channel Modeling and its Application in Simulation Effects of Multipath Propagation on GNSS Receivers Two-Ray Model Two-Ray example, receiver reads line-of-sight signal (LOS) one additional ray Example error envelope for different delays 1.2 1 0.8 ray 1 ray 2 (real) ray 2 (imag) P 0.6 0.4 0.2 0 5 0 5 10 15 20 25 30 delay/m wave propagation effects in urban and rural areas lead to strong multipath reception reflection, scattering, diffraction on buildings, trees, etc. many echoes impinge within few nanoseconds after LOS
TUM Navigation Colloquium 7 GNSS Channel Modeling and its Application in Simulation GNSS performance in diffcult, high-multipath environments How to Analyse Multi-Path Disturbances? multipath propagation and shadowing are dominant error sources analysis analytically: works only for single echo (error envelope) GNSS measurements in position domain: only sum of effects visible, not the respective contributions sample-level simulation using a channel model computationally expensive due to high signal bandwidths new simulator for fast processing of channel data needed
TUM Navigation Colloquium 8 GNSS Channel Modeling and its Application in Simulation DLR Land Mobile Satellite Channel Sounding Measurements Measurement campaign To get to know the GNSS propagation channel: measurements have to be conducted DLR conducted field measurements in 2002 for urban, sub-urban, rural, and pedestrian scenarios frequency: 1460 1560 MHz (L-band) bandwidth: 100 Mhz power: 10 W (EIRP)
TUM Navigation Colloquium 9 GNSS Channel Modeling and its Application in Simulation DLR Land Mobile Satellite Channel Sounding Measurements Results Raw measurements ESPRIT super-resolution result Delay [ns] Delay [ns]
TUM Navigation Colloquium 10 GNSS Channel Modeling and its Application in Simulation DLR GNSS Urban Channel Model Structure
Time-Variant Channel Impulse Responses (CIR) Sample output of DLR GNSS urban channel model time variable t, delay variable τ, update rate f CIR A t 1/f CIR t TUM Navigation Colloquium 11 GNSS Channel Modeling and its Application in Simulation
TUM Navigation Colloquium 12 GNSS Channel Modeling and its Application in Simulation DLR GNSS Urban Channel Model Output time-variant CIRs Power Delay Profile: 2D histogram p(p, τ) Power delay profile probability density function 0 10 1 Resulting power delay profile of a Power [db] 5 10 15 20 25 30 0 100 200 300 400 500 Delay [ns] 10 2 10 3 10 4 10 5 10 6 10 7 sample urban simulation run CIR rate: 300 Hz simulated time: 5 s max vehicle speed: 50 km/h satellite elevation: 30 satellite azimut: 45
TUM Navigation Colloquium 13 GNSS Channel Modeling and its Application in Simulation Radio Channel Characteristics of Rural Environments Rural measurements cover villages vegetation trees, alleys, forests electricity poles Modeling approaches statistic of all measurements analyze measurements and identify contributors Synthesis approach at first, single trees will be analyzed
TUM Navigation Colloquium 14 GNSS Channel Modeling and its Application in Simulation Radio Channel Characteristics of Rural Environments
TUM Navigation Colloquium 16 GNSS Channel Modeling and its Application in Simulation Rural Measurements, Analysis of Single Trees van trajectory channel impulse responses track in open field needed, without buildings
TUM Navigation Colloquium 17 GNSS Channel Modeling and its Application in Simulation Wave Propagation Effects Caused by Single Trees Tree Parameterization Goal develop wide-band channel model for trees leaves cause mainly attenuation (water content) branches reponsible for scattering (wavelength) Model properties constant specific attenuation for tree canopy and trunk number of point scatterers inside canopy
TUM Navigation Colloquium 18 GNSS Channel Modeling and its Application in Simulation Rural Measurements, Analysis of Single Trees Delay Spread Determination minimum excess distance maximum excess distance
TUM Navigation Colloquium 19 GNSS Channel Modeling and its Application in Simulation Treetop Scattering d tree-rx (t) d a tx-tree (t) d LOS (t) receiver point sources drawn when incident angle changes multiple scattering inside treetop up to 3 rd order transmitter specific attenuation modeled for treetop and trunk
TUM Navigation Colloquium 20 GNSS Channel Modeling and its Application in Simulation Rural channel model output, signal model Complex amplitude of ith point source a i (t) = Pmax N 1 [d e,i (t)] 2 ej 2π «de,i (t) λ (1) Resulting signal at the receiver (LOS + N point sources in canopy): s(t, τ) = k e j 2π dlos (t) λ δ(τ) + N a i (t)δ(τ τ i ) (2) i=1
TUM Navigation Colloquium 21 GNSS Channel Modeling and its Application in Simulation Time-variance of the Radio Channel Artificial Scenery
TUM Navigation Colloquium 22 GNSS Channel Modeling and its Application in Simulation Rural Channel Model Output Comparison: Raw Measurements vs. Channel Model Output raw channel sounding measurements model output
TUM Navigation Colloquium 23 GNSS Channel Modeling and its Application in Simulation GNSS performance in diffcult, high-multipath environments How to Analyse Multi-Path Disturbances? GNSS channel model/measurements description of time-domain simulation
TUM Navigation Colloquium 24 GNSS Channel Modeling and its Application in Simulation Time-Domain Simulation, Structure Channel model output is used Simulation chain from sender to receiver
TUM Navigation Colloquium 25 GNSS Channel Modeling and its Application in Simulation Time-Variant Channel Impulse Responses (CIR) How to use continous CIRs in a discrete time-domain simulation?
TUM Navigation Colloquium 26 GNSS Channel Modeling and its Application in Simulation Time-Variant Channel Impulse Responses (CIR) Using Channel Model Data: CIR FIR Coefficients Interpolation magnitude 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 CIR impulses sinc for CIR impulse 1 sinc for CIR impulse 2 sum of sinc functions FIR coefficients 1 0 1 2 3 4 5 6 delay τ [s] x 10 8 Time-continuous CIR impulses must be interpolated to time-discrete FIR coefficients Low-pass interpolation: FIR(t) = mx k=0 ω max = 2π f smpl 2 A CIR (k) sin[ωmax(t T CIR (k))] ω max(t T CIR (k)) Example: f smpl = 100 MHz
TUM Navigation Colloquium 27 GNSS Channel Modeling and its Application in Simulation Time-Variant Channel Impulse Responses (CIR) CIR Usage in SNACS magnitude 1.6 1.4 1.2 1 0.8 0.6 CIR impulses sinc for CIR impulse 1 sinc for CIR impulse 2 sum of sinc functions FIR coefficients 0.4 0.2 0 1 0 1 2 3 4 5 6 delay τ [s] x 10 8
TUM Navigation Colloquium 28 GNSS Channel Modeling and its Application in Simulation SNACS GNSS Simulation Chain Implementation modular object-oriented approach, written in C++ parallel processing every processing block is implemented as its own thread complex convolution expands to multiple threads blocks are connected with circular buffers (asynchronous access)
GNSS Simulation Chain SNACS Demonstration simulation parameters Configuration File Simulation: { SamplingFrequency = 40e6; // Hz SignalLength = 10.0; // s IntermediateFrequency = 9e6; // Hz SNBlocks = ( sampling frequency signal two-sided bandwidth ADC resolution early-late spacing DLL discriminator correlation time 40 MHz GPS C/A 10.23 MHz 3 bit 0.1 chips early-late 0.001 s { Type = snsignalgenerategps ; SignalType = C/A ; } { Type = snprocessorlpf ; CutOffFrequency = 10.23e6; } { Type = snprocessoradc ; }, { Type = snsdrgps ; SignalType = C/A ; DiscriminatorType = EML ;... } TUM Navigation Colloquium 29 GNSS Channel Modeling and its Application in Simulation ); };
TUM Navigation Colloquium 30 GNSS Channel Modeling and its Application in Simulation SNACS Demonstration 1
GNSS Simulation Chain SNACS Demonstration simulation parameters Configuration File Simulation: { SamplingFrequency = 40e6; // Hz SignalLength = 10.0; // s IntermediateFrequency = 9e6; // Hz SNBlocks = ( sampling frequency signal two-sided bandwidth ADC resolution early-late spacing DLL discriminator correlation time 40 MHz GPS C/A 10.23 MHz 3 bit 0.1 chips early-late 0.001 s { Type = snsignalgenerategps ; SignalType = C/A ; } { Type = snprocessorlpf ; CutOffFrequency = 10.23e6; } { Type = snprocessorchannel ; Filename = /CIRs/ DLR-Urban-Elevation-25.h5 ; }, { Type = snprocessoradc ; }, { Type = snsdrgps ; SignalType = C/A ; DiscriminatorType = EML ;... } TUM Navigation Colloquium 31 GNSS Channel Modeling and its Application in Simulation ); };
TUM Navigation Colloquium 32 GNSS Channel Modeling and its Application in Simulation SNACS Demonstration 2
TUM Navigation Colloquium 33 GNSS Channel Modeling and its Application in Simulation SNACS simulation result GPS C/A signal standard DLL
TUM Navigation Colloquium 34 GNSS Channel Modeling and its Application in Simulation Simulation with Raw Measurement Data Drive through an Alley
TUM Navigation Colloquium 35 GNSS Channel Modeling and its Application in Simulation Simulation with Raw Measurement Data Drive through an Alley
TUM Navigation Colloquium 36 GNSS Channel Modeling and its Application in Simulation Bouncing off Walls and Trees: Multipath Channel Modeling for Satellite Navigation from the Samples Point of View Conclusion flexible wide-band rural channel model is being developed GNSS sample-level software simulator, C++, multi-threading usage of channel model data and raw channel measurements Future Rural Channel Model process all available measurement data for single tree scattering include electricity poles, forrests, and buildings SNACS time-domain GNSS simulation Galileo signals implementation multi-link simulation
Bouncing off Walls and Trees: Multipath Channel Modeling for Satellite Navigation from the Samples Point of View SNACS is an open-source project hosted on http://snacs.sourceforge.net Thank you very much for your attention! frank.schubert@dlr.de TUM Navigation Colloquium 37 GNSS Channel Modeling and its Application in Simulation