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Sensor Signal Processing Group (EEE, Adelaide Uni)

Sensor Signal Processing Group (EEE, Adelaide Uni). Overview of autonomous vehicle related activities D.Gibbins , October 2010. SSP Group Overview. Team of 4-5 researchers plus Phd Students (Research Leader: Prof. D.A.Gray ) Specialising in Signal (& Information) Processing

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Sensor Signal Processing Group (EEE, Adelaide Uni)

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  1. Sensor Signal Processing Group (EEE, Adelaide Uni) Overview of autonomous vehicle related activities D.Gibbins, October 2010

  2. SSP Group Overview • Team of 4-5 researchers plus Phd Students (Research Leader: Prof. D.A.Gray) • Specialising in Signal (& Information) Processing • Radar (L-band, SAR, ISAR , phased-array, MIMO) • Electro-optical, LIDAR/LADAR, Sonar sensors etc.. • GPS/INS • Target classification, recognition, 2D image and 3D scene analysis, route planning etc • Focus on applications related to Autonomous vehicles • GPS Anti-jam, jammer localisation (single/multiple UAV’s) • Sensor fusion, path planning using PMHT, SLAM etc... • Terrain & scene analysis • Target recognition (2D & 3D) – apps in aerial surveillance • Radar sensors for autonomous vehicles (research interest) • Detection/mapping/collision avoidance?

  3. Unprotected Receiver Measurements Protected Receiver Measurements East Measured Van Location South GPS Principle Researcher: Matthew Trinkle Conventional and improved interference localisation • Interference Mitigation & Localisation for UAV applications • Temporal, spatial and STAP processing • Adaptive beam-forming • Null steering • DOA estimation • Successful anti-jam trials held in Woomera in presence of multiple interference sources • Ongoing development of compact anti-jam hardware for aerial platforms

  4. UAV surveillance & targeting Principle Researcher: Danny Gibbins • Electro-optical Seeker Target Recognition (DSTO sponsored) • Static land based & littoral moving targets etc • LADAR/LIDAR terrain reconstruction and classification (DSTO sponsored) • Stabilisation, reconstruction & scene analysis for apps such as route planning, situation awareness etc • LADAR/LIDAR 3D target recognition (DSTO & self funded R&D) • ICP registration, SIFT matching, correlation based etc (high res and more recently low-resolution data) • Video based stabilisation/super-resolution/geo-location (DSTO sponsored)

  5. EO Mid-course Navigation, LADAR Terrain Analysis & Classification 3D Terrain reconstruction from airborne LADAR & optical data Example of EO Model Recognition for navigation correction – Real Data “A Comparison of Terrain Classification using Local Feature measurements of 3-Dimensional Colour Point-cloud Data” D.Gibbins IVCNZ 2009.

  6. 3D LADAR/LIDAR Target Recognition (& registration) 3D Sift feature analysis 3D Sift feature matching “3D Target Recognition Using 3-Dimensional SIFT or Curvature Key-points and Local Spin Descriptors” D.Gibbins DASP 2009.

  7. PMHT Path Planning for UGV’s (Cheung,Davey,Gray) x01 x11 xT1 Platform States • Probabilistic multi-hypothesis tracking for UGV path planning • Treats locales of interest as measurements and UGV platforms as targets • Attempts to optimise search across multiple UGV’s x0m x1m xTm z1 z2 zn Waypoints  Example of path planning for 4 UGV’s based on random locations of interest Waypoint to platform assignments k1;πk k2;πk kn;πk τ1;πτ τ2;πτ τt;πτ Waypoint to time assignments

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