Analog VLSI Spatio-Temporal Seeker Image Data Filtering for Threat Cloud Discrimination

In Phase II, CSC proposes to continue developing the distant target identification capabilities of the non-linear spatio-temporal filtering motion-energy analysis techniques initiated during Phase I. The developed technique is based on cross-correlationsover the focal-plane-array measured signal intensity exchange between pixels sampling distant targets. Work to be performed during Phase II includes both the extension of the analysis technique to more distant targets and the specific application tothreat cloud RV/RV-decoy discrimination. Hardware-in-the-loop testing and analysis using the existing Thin Film Analog Image Processor (TAIP) spatial convolution engine is conjunction with our temporal image processing chips will proceed throughout PhaseII to validate our simulated results. During Phase I, CDC explored the applicability of analog VLSI spatio-temporal filtering (STF) and pixel-on-target intensity modulation analysis of computed motion-energy to target identification based on measuredpixel modulations due to radiometrically accurate, conical fixed range RV micro-dynamics. Our novel approach leverages the natural ability of massively parallel analog circuitry to perform important computationally intensive image processing tasks inreal-time, and therefore has potential for handling intercept engagements containing numerous targets. Phase I results indicate potential for distant detected target object identification, and guides our threat cloud discrimination approach.Early targetidentification 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 may also beapplicable in may other commercial areas including automatic inspection, biometric identification, security, surveillance, and other machine vision applications. CSC is fulfilling current DARPA and AIT sponsored contracts while aggressively pursuingpotential commercial opportunities for analog VLSI image processing applications. The unique and powerful capability to perform massive convolution functions in real-time, in a small package and with low power requirements will enable a new generation ofintelligent systems not previously considered viable by systems and product designers.