Multisensor segmentation using LADAR and PMMW

摘要

Fusing information from sensors with very different phenomenology is an attractive and challenging option for autonomous target acquisition (ATA) Systems because correct target detections should correlate between sensors while false alarms might not. In this paper, we present a series of algorithms for detecting and segmenting targets from their background in passive millimeter wave (PMMW) and laser radar (LADAR) data. PMMW sensors provide a consistent signature for metallic targets. They also can effectively operate under adverse weather conditions, however they exhibit poor angular resolution. LADAR sensors produce high-resolution range and reflectance images, but are sensitive to adverse weather conditions. Sensor fusion techniques are applied with the goal of maintaining high probability of detection while decreasing the false alarm rate.