Spectral Optimization Studies and Simulations for Two-, Three-, and Four- Band Staring LWIR Sensors in Missile Defense Scenarios

摘要

Prototype 2-, 3-, and 4- band long wave infrared (LWIR) focal plane arrays (FPA) for missile defense applications have recently been constructed to enhance target discrimination in space-based interceptor seekers. To address issues related to target identification such as algorithm choice and band number, this study created synthesized, optimized (using a genetic algorithm) image cubes (8- 12 μm) of targets and backgrounds compatible with expected mid-course defense scenarios and current multicolor sensors. Each candidate band was weighted using an interacting band edge model for 2-, 3- or 4- band sensors, consistent with a DRS multi-color HgCdTe LWIR FPA. Whitening the binned cubes and assigning red, green, blue colors directly to the whitened data set can prominently display and identify targets. Modified target signatures applied in matched filters searches and spectral angle maps autonomously searched for targets in the synthetic binned image cubes. Target discrimination diminished with decreasing target temperature and/or increasing distance between sensor and targets due to mixing subpixel target spectra with noise background. Spectral angle maps identified target temperatures and materials substantively better than the matched filter in this particular study. Target material and temperature identification improved by increasing number of bands, with greatest improvement for 3 bands relative to 2 bands. Extending detector sensitivity to 6-14 μm failed to improve target identification. This is the first study to systematically examine target identification in synthetic images cubes, consistent with missile defense scenarios and current multi-sensor technology.