Analog Image Processing for Improved Hypertemporal ELDT SNR

During Phase I Computational Sensors Corp. (CSC) will develop spatial and temporal domain filtering approaches for improving the signal-to-noise-ratio (SNR) in high frame rate image data enabling all-weather hypertemporal ELDT techniques to robustly identify a missile launch in solar background scatter. The processing will be designed to discriminate between solar background scatter and missile plume signatures for high-altitude airborne and space based sensing platforms. The processing approaches to be explored will reflect a physical implementation where detector data is processed in the analog domain relying on pixel-to-pixel micro-via connectivity being developed through the DARPA VISA program. Performing signal processing prior to digitization improves the signal dynamic range and SNR through background subtraction. Boost-phase intercepts have an extremely compressed time line requiring fire control commit to be determined within the first minute following launch for an endo-atmospheric or low exo-atmospheric intercept. Current surveillance systems provide launch detection after the threat has breached the cloud layer. Hypertemporal approaches which exploit the high-frequency signature of missile plumes scattered through cloud layers has the potential to provide all weather early launch detection, and possibly, detection at ignition capability. Under a Phase II program, simulation and design would progress with production of a demonstration chip.