Space Based Radar (SBR) Bistatic Space Time Adaptive Processing (STAP)

Black River Systems Co., Inc. and Syracuse Research Corporation propose to develop medium earth orbit/geosynchronous earth orbit bistatic space-based radar concepts with emphasis upon innovative knowledge-aided space-time adaptive processing algorithms to achieve high detection probability and low false alarm rates in the presence of severe clutter and jamming environments. Computer simulations will be developed and integrated into existing and evolving simulations providing a complete end-to-end modeling and simulation capability. The primary emphasis during Phase I includes: (1) performing an initial analysis of medium earth orbit (MEO)/ geosynchronous earth orbit (GEO) bistatic SBR architectures, (2) investigating two new innovative STAP architectures (Severely Nonstationary Interference Processing, SNIP, and an enhanced Parametric Adaptive Matched Filter, SRC_PAMF) to achieve high detection performance and low false alarm rates, in addition to evaluating currently existing and evolving STAP algorithms, in MEO/GEO bistatic SBR scenarios, (3) incorporating knowledge-aided techniques into the SBR detection and tracking functions, (4) demonstrating knowledge-aided SBR bistatic STAP architecture feasibility via simulation, and (5) developing a Phase II program plan for completion of the design initiated in Phase I. Measures of Performance (MOPs) will be utilized to provide a basis for performance comparison BENEFIT: The technology developed will become instrumental in the development of a variety of military and commercial applications including SBR architectures, airborne surveillance radar applications, anti-drug surveillance systems and communications systems. Knowledge-aided STAP signal/data processing system has many potential military applications.