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Titolo:
Performance of a class of adaptive detection algorithms in nonhomogeneous environments
Autore:
Richmond, CD;
Indirizzi:
MIT, Lincoln Lab, Lexington, MA 02173 USA MIT Lexington MA USA 02173MIT, Lincoln Lab, Lexington, MA 02173 USA
Titolo Testata:
IEEE TRANSACTIONS ON SIGNAL PROCESSING
fascicolo: 5, volume: 48, anno: 2000,
pagine: 1248 - 1262
SICI:
1053-587X(200005)48:5<1248:POACOA>2.0.ZU;2-1
Fonte:
ISI
Lingua:
ENG
Keywords:
ACE; adaptive detection; AMF; beamforming; CFAR; false alarms; GER; GLRT; inhomogeneities; sidelobe blanker; undernulled interference;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
--discip_EC--
Citazioni:
16
Recensione:
Indirizzi per estratti:
Indirizzo: Richmond, CD MIT, Lincoln Lab, 244 Wood St, Lexington, MA 02173 USA MIT 244 Wood St Lexington MA USA 02173 exington, MA 02173 USA
Citazione:
C.D. Richmond, "Performance of a class of adaptive detection algorithms in nonhomogeneous environments", IEEE SIGNAL, 48(5), 2000, pp. 1248-1262

Abstract

A two-dimensional (2-D) adaptive sidelobe blanker (ASB) detection algorithm was developed through experimentation as an extenuate for false alarms caused by undernulled interference encountered when applying the adaptive matched filter, (AMF) in nonhomogeneous environments. The algorithm's utility has been demonstrated empirically. Considering theoretic performance analyses of the ASB detection algorithm as well as the, generalized likelihood ratio test (GLRT), and the adaptive cosine estimator (ACE), under nonideal conditions, can become fairly intractable rather quickly, especially in an adaptive processing context involving covariance estimation. In this paper, however, we have developed and exploited a theoretic framework through whichthe performance of these algorithms under nonhomogeneous conditions can beexamined theoretically. It is demonstrated through theoretic analysis thatin the presence of undernulled interference, the ASB is a pliable false alarm regulatory (FAR) detector that maintains good target sensitivity. A viable method of ASB threshold selection is also presented and demonstrated.

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Documento generato il 27/09/20 alle ore 20:08:45