Spatio-Temporal Interceptor Image Filtering for Threat Cloud RV/Chaff Discrimination

During Phase I, CSC will explore the applicability of non-linear analog VLSI spatio-temporal filtering (STF) of interceptor sensor imagery to threat-cloud RV/decoy and chaff discrimination. Our approach will develop new STF analysis techniques to achieverobust RV micro-dynamics signature discrimination against accurately simulated threat-cloud chaff. Previous work, based on a cross-correlation analysis of the STF motion-energy exchange between pixels sampling distant targets in image sensor noise, hasindicated potential for RV/decoy discrimination based on target micro-dynamics and has direct applicability to RV/chaff discrimination. Furthermore, significant interceptor 2-D spatial aspect target-target discrimination and target-clutter discriminationachieving track-before-detect (TBD) capability of intermittently resolved targets in heavy terrestrial terrain clutter has been demonstrated using spatial-temporal filtering coupled with dynamic programming. Our novel approach leverages the naturalability of massively parallel analog circuitry to perform computationally intensive image processing tasks in real-time, and centers on chaff effectively behaving as a clutter background, during a significant portion of the mid-course engagement time-line,surrounding lethal RV target(s) and/or decoys to IR or Visible seeker sensor systems.Hardware-in-the-loop testing and analysis using the existing spatial convolution engine in conjunction with our temporal image processing chips will proceed throughout Phase I to validate our simulated results. Early target identification capabilities using non linear motion energy image processing techniques integrated in analog image processors are ideally suited for compact, low power, military imaging applications. Analog image processing technology mayalso be applicable in many other commercial areas including automatic inspection, biometric identification, security, surveillance, and other machine vision applications. To date, non-linear motion energy image processing technology using TAIP chiptechnology developed under DARPA contract in conjunction with temporal filtering capability developed under ARMY-SMDC contract has demonstrated significant utility in detection, track-before-detect capability when coupled with dynamic programming, anddiscrimination of low flying missile targets in moving background clutter.CSC is fulfilling current DARPA and AIT sponsored contracts while aggressively pursuing potential commercial opportunities for analog VLSI image processing applications. The unique and powerful capability to perform massive convolution functions inreal-time, in a small package and with low power requirements will enable a new generation of intelligent systems not previously considered viable by system and product designers systems for performing sophisticated imaging tasks including automatic targetrecognition, target tracking, feature extraction, 3D reconstruction, image classification, and image understanding are critical for the building of compact, low powered deployable missile defense systems.