This paper describes the development of adaptive importance sampling (IS) techniques for estimating false alarm probabilities of detectors that use space-time adaptive processing (STAP) algorithms. Fast simulation using IS methods has been notably successful in the study of conventional constant false alarm rate (CFAR) radar detectors, and in several other applications. The principal objectives here are to examine the viability of using these methods for STAP detectors, develop them into powerful analysis and design algorithms and, in the long term, use them for synthesizing novel detection structures. The adaptive matched filter (AMF) detector has been analyzed successfully using fast simulation. Of two biasing methods considered, one is implemented and shown to yield good results. The important problem of detector threshold determination is also addressed, with matching outcome. As an illustration of the power of these methods, two variants of the square-law AMF detector that are thought to be robust under heterogeneous clutter conditions have also been successfully investigated. These are the envelope-law and geometric-mean STAP detectors. Their CFAR property is established and performance evaluated. It turns out the variants have detection performances better than those of the AMF detector for training data contaminated by interferers. In summary, the work reported here paves the way for development of advanced estimation techniques that can facilitate design of powerful and robust detection algorithms
Importance sampling for characterizing STAP detectors
IEEE Transactions on Aerospace and Electronic Systems ; 43 , 1 ; 273-285
01.01.2007
1438515 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Importance Sampling for Characterizing STAP Detectors
Online Contents | 2007
|Stap voor stap meer zitplaatsen
IuD Bahn | 2000
|OV-chipkaart komt stap voor stap dichterbij
IuD Bahn | 2005
|Stap voor stap aan de slag met teerhoudend asfalt
Online Contents | 1998
Online Contents | 2000
|