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Model-based object recognition using laser radar range imagery

The combined effects of laser speckle and local oscillator shot noise degrade coherent laser radar range measurements. As a result, laser radar range imagery suffers from both uniformly-distributed range anomalies and Gaussian-distributed local range errors. Our goal in this research is to develop a target recognition system capable of recognizing military vehicles in range images provided by airborne laser radars. In particular, we will focus on using laser radar range imagery in a statistical model-based object recognition system. We shall present performance results for our object recognition system using laser radar data from the MIT Lincoln Laboratory Infrared Airborne Radar (IRAR) data release together with 3-D CAD models which account for the possible military targets that may be present on the site imaged by the laser radar.