DocumentCode :
311192
Title :
Adaptive detector statistics using moment-based approximations
Author :
Smith, Steven T.
Author_Institution :
Lincoln Lab., MIT, Lexington, MA, USA
fYear :
1996
fDate :
3-6 Nov. 1996
Firstpage :
1118
Abstract :
Adaptive filtering techniques are used for many detection applications such as communications and radar, yet the complicated statistics of adaptive detectors frustrate a closed form analysis of their performance. This paper offers a partial solution to this problem by providing closed form moments of the adaptive matched filter (AMF) and generalized likelihood ratio test (GLRT) that can be used in a Laguerre series expansion to efficiently complete the probabilities of detection and false alarm of these adaptive detectors. The radar case is considered in particular. Furthermore, exact closed form statistics of the AMF are given which are convenient for probability of false alarm computations and describing the asymptotic behavior of this test.
Keywords :
adaptive filters; adaptive signal detection; approximation theory; matched filters; method of moments; radar detection; statistical analysis; stochastic processes; Laguerre series expansion; adaptive detector statistics; adaptive filtering techniques; adaptive matched filter; asymptotic behavior; closed form moments; closed form statistics; communications; false alarm; generalized likelihood ratio test; moment-based approximations; probabilities; radar; Adaptive filters; Detectors; Matched filters; Performance analysis; Probability; Radar applications; Radar detection; Statistical analysis; Statistics; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 1996. Conference Record of the Thirtieth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
ISSN :
1058-6393
Print_ISBN :
0-8186-7646-9
Type :
conf
DOI :
10.1109/ACSSC.1996.599117
Filename :
599117
Link To Document :
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