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
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