Kyusoon Lee
School of Electrical and Computer Engineering
Cornell University
USA
email: kl224@cornell.edu
Space-Time Adaptive Processing (STAP) referes to adaptive radar processing algorithms which operate on data collected from both multiple sensors and multiple pulses to cancel interference and detect targets.
Fully adaptive STAP is known to be optimal but the required number of operations makes it impractical for real-time implementation. Hence, many different heuristic are sought to approximate the optimal method. The real-time requirement can only be met by parallel processing of data.
In this work we introduce a software framework called ALPS for prototyping and optimizing various parallel STAP methods. Within this framework, users describe STAP heuristics with basic building blocks. The software finds the optimal parallel implementation of the heuristic.