Sensor Signal Processing Group (EEE, Adelaide Uni)

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Sensor Signal Processing Group (EEE, Adelaide Uni)

• Overview of autonomous vehicle related activities
• D.Gibbins, October 2010

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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 UAVs)
• 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?

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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

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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 RD)
• ICP registration, SIFT matching, correlation
  based etc (high res and more recently
  low-resolution data)
• Video based stabilisation/super-resolution/geo-loc
  ation (DSTO sponsored)

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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.
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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.
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PMHT Path Planning for UGVs (Cheung,Davey,Gray)

• 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 UGVs

? Example of path planning for 4 UGVs based on
random locations of interest