Multi-Phenomenology Sensing and Sensor Control in Unmanned Intelligence Vehicle (UIV) for ATR and Tracking of Dismounts and Vehicles

Detection, tracking, and identification of targets in an urban environment is very difficult due to the density of targets, as well as the interrupted sensor to target line-of-sight due to intervening buildings. A single sensor has difficulty performing these tasks. Using multiple sensors with different phenomenologies can provide the capability to perform this critical mission. This relies on a suite of advanced signal processing algorithms that can exploit the unique phenomenology from each sensor in the suite, fuse this data to improve performance, and cue an operator with a high confidence detection of targets. Under this Phase II SBIR program, ISL and DMT will develop an unmanned aerial vehicle hosted sensor suite and associated algorithms that exploits multiple phenomenologies to detect, identify, track and geolocate targets. The focus of this effort is a sensor suite using radio frequency and electro-optical and infra-red sensors along with automatic sensor cueing, automatic target classification, tracking, and prioritization to minimize human decision making. During the Phase II effort, algorithms will be developed and the performance improvements achievable using multi-sensor data will be demonstrated using collected data. A system architecture will be developed for Phase III integration and testing.