ALPS: a software framework for parallel space-time adaptive processing

Authors:
Kyusoon Lee;Adam W. Bojańczyk
Affiliations:
School of Electrical and Computer Engineering, Cornell University, Ithaca, NY;School of Electrical and Computer Engineering, Cornell University, Ithaca, NY
Venue:
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
Year:
2004

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Abstract

Space-Time Adaptive Processing (STAP) refers to adaptive radar processing algorithms that take the signals from both multiple sensors and multiple pulses to cancel interferences and detect a target. Fully-adaptive STAP is known to be optimal, but the required number of operations is overwhelming, and makes this method impractical. Hence, many different heuristic approaches are sought to approximate the optimal method with smaller number of operations. In this work, we present a software framework called ALPS to help prototype various parallel STAP methods, and predict their performances.