SBIR-STTR Award

Use of polarization signatures can dramatically improve the performance of active or laser sensors for automated target recognition (ATR) and other applications. While their potential has been widely recognized, laser polarimeters have been limited by technology gaps in two areas

Keywords:
Polarimetry, Polarimeter, Laser Remote-Sensing, Atr, Pct, Active Imaging

"Despite its sensitivity to diverse shape, surface, and material properties, laser polarimetry is one of the primary remaining remote-sensing modalities yet to be effectively utilized. The traditional limitations of laser polarimetry in a field sensor have been 1) making efficient use of multi-dimensional polarimeter data, and 2) achieving required sensor footprint and speed. Phase 1 demonstrated automated target recognition (ATR) algorithms based on mission-specific laser-polarimeter data that achieve significant performance improvements over algorithms based on non-polarized laser data. In particular, these algorithms achieve target pose invariance and low false-alarm rate (FAR). These algorithms, generally termed polarization-components techniques (PCT), overcome the first limitation to fielding a polarimetric ATR sensor. The PCT algorithms also minimize measurement requirements, thereby guiding the design of partial Mueller matrix polarimeters (pMMP), which represent a significant step in overcoming the second limitation. The Phase 2 program will finalize and build a conceptual pMMP design and apply the resulting field polarimeter to mission-specific field tests. Future commercialization efforts will be supported by a field polarimeter available for demonstrations of general-purpose ATR and by the next generation PCT test and simulation software to be developed and utilized in the Phase 2 program."

Keywords:
"laser Polarimetry, Machine-Learning, Mueller-Matrix, Support Vector Machine, Atr, Far"