Bannon, A

Griffiths, H

Ritchie, M

Woollard, M

English

UCL Discovery

Novel transceiver architectures for automatic target recognition in UAV-based SAR systemsAlan Bannon, Michael Woollard, Prof. Hugh Griffiths, Dr Matthew RitchieDepartment of Electronic and Electrical EngineeringContextThis project involved SAR simulation, FMCWradar construction, ASIC design and radar signalprocessing. The focus of the work was to addressthe high power consumption issues faced byprevious work implementing onboard ATRprocessing for vehicle classification on low-equitysurveillance radar systems for UAV applications.A prototype of the RF transceiver wasconstructed using COTS hardware and minimalin-house fabrication; data from this system hasbeen used to support the development of thesignal processing architecture.SAR SimulationSimulated SAR imagery was constructed using theRaySAR engine proposed by Stephen Auer. Theoriginal simulator was modified to run in apipelined fashion on the High PerformanceCompute clusters at UCL, and is now capable ofproducing 6000 images per hour on a single node.A convolutional neural network, Tiny-YOLO, wasused to classify simulated SAR images ofvehicles. Work is ongoing to improve the realismof the generated imagery through a programme ofmodifications to the existing RaySAR package,and to integrate the ATR analysis into a fullclosed-loop system.HardwareThe radar transceiver operates at X-band withprogramable bandwidths of up to 1 GHz. It is adirect conversion architecture based around a TILMX2492 PLL; the waveform is programmed as aseries of linear sections. Cavity antennas withdual FSS front planes are used for both transmitand receive channels.An accelerator for the filtered backprojectionprocess has been developed as an ASIC designusing VLSI techniques. The proposed architectureis parallelised on a per-pixel basis, making itscalable to the available die area, and is fullypipelined for maximum throughput. The currentdesign was completed using an X-Fab 180 nmprocess, in anticipation of a trial production run.ROC curves for multiclass classification using Tiny-YOLO classifier on simulated 15 cm resolution SAR imagery of vehicular targets from RaySARPackaged FMCW radar unit during field trialsExample MTI for pedestrian target from initial field trialsBlock diagram of proposed filtered backprojection accelerator, realised as an ASIC designRouting display for 4-pixel PARROT implementation (Cadence Innovus)SAR SimulationBuild of an FMCW RADARASIC Design For SAR ATRRadar Signal ProcessingRadar ResultsThe radar unit has been tested in a number ofconfigurations against a wide range of target. Thefirst field trials demonstrated short-range mobilitysensing and micro-Doppler capture againstpedestrian targets. Later tests have shownmobility surveillance at greater ranges againstsmall boats, and promising results have beenachieved in SAR capture exercises, despiteundersampled apertures.ConclusionsThis project has demonstrated significantperformance advantages over previous FPGA-based architectures. Several routes for ongoingimprovements have been identified, and thissystem appears set to support related research atUCL for several years to come.Simulated bistatic SAR images showing vehicular targets and the associated predictions Example spotlight mode SAR reconstruction for a small building in the UCL main quad Reconstruction result from PARROT Verilog model for simulated MNIST target RF schematic for the radar unit used for trials. A second revision is being prepared for airborne tests during the summer 

Novel transceiver architectures for automatic target recognition in UAV-based SAR systems

https://discovery.ucl.ac.uk/10082685/1/EMSIG_poster_A1_MW_AB_MR.pdf

Novel transceiver architectures for automatic target recognition in UAV-based SAR systems

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