Integration of 360-Retrodirective Noise Correlating Radar with Panormic Camera for Real-Time Detection and Imaging of Ballistic Threats

Retrodirective pseudorandom-noise-correlating radar has already been demonstrated on small ballistic targets, such as sniper bullets. And detection occurs with enough range (a few tens of meters) to acquire bearing information (rangebin, azimuth, and elevation) and therefore develop a track in near-real-time. What is lacking is the connection between such radar performance on warfighter situational awareness and force protection. The proposed effort will investigate the design of a 360o-FOV (in azimuth) retrodirective radar and its integration with a panoramic camera to provide the warfighter real-time display of bullet tracks overlaid on an image of the local environment. This entails many issues in radar design, and in sensor and data fusion. The proposal teams an expert organization in retrodirective noise-correlating radar (Physical Domains) with experts on data and sensor fusion from the Academic (Fordham University) and Commercial (Altrus Networks) sectors. The overall STTR Phase-I effort will be a Virtual Integration of the radar and a panoramic camera with deliverables that include an optimal design for the retrodirective radar, drivers and interfaces between the hardware and software components, and algorithms for the high-data-rate (up to 1 GBit/s) radar-camera data fusion. The preferred human interface and system controller will be a customized PDA.