A distributed automatic target recognition system using multiple low resolution sensors
2008
In this paper, we propose a multi-agent system which uses swarming techniques to perform high
accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can
co-operatively share the information from low-resolution images of different looks and use this information
to perform high accuracy ATR. An advanced, multiple-agent Unmanned Aerial Vehicle (UAV)
systems-based approach is proposed which integrates the processing capabilities, combines detection
reporting with live video exchange, and swarm behavior modalities that dramatically surpass individual
sensor system performance levels. We employ real-time block-based motion analysis and compensation
scheme for efficient estimation and correction of camera jitter, global motion of the camera/scene and the
effects of atmospheric turbulence. Our optimized Partition Weighted Sum (PWS) approach requires only
bitshifts and additions, yet achieves a stunning 16X pixel resolution enhancement, which is moreover
parallizable. We develop advanced, adaptive particle-filtering based algorithms to robustly track multiple
mobile targets by adaptively changing the appearance model of the selected targets. The collaborative ATR
system utilizes the homographies between the sensors induced by the ground plane to overlap the local
observation with the received images from other UAVs. The motion of the UAVs distorts estimated
homography frame to frame. A robust dynamic homography estimation algorithm is proposed to address
this, by using the homography decomposition and the ground plane surface estimation.
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