Abstract
MIT Lincoln Laboratory is investigating how to use a-priori information in an adaptive MTI radar under the DARPA-funded knowledge-aided sensor signal processing and expert reasoning (KASSPER) program. Our objective is to demonstrate an embedded processor and some algorithms capable of real-time space-time adaptive processing (STAP) enhanced by a-priori knowledge of terrain types, locations of clutter discretes and road layouts. The immediate goal is to realize a baseline system, which is a conventional STAP chain making no use of a-priori information. It is designed to allow the entire KASSPER community to insert new algorithm features that exploit a-priori knowledge. The paper describes both the hardware and the algorithms that are being coded to realize the baseline system. This baseline algorithm suite is intended to provide a reasonable starting point for adding a-priori knowledge in the form of new training schemes or new STAP algorithms to improve target detectability near the mainbeam clutter ridge.
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