DocumentCode :
3212718
Title :
Applying hidden Markov models to radar detection in clutter
Author :
Stein, D.W.J. ; Dillard, G.M.
Author_Institution :
NCCOSC RDTE, USA
fYear :
1997
fDate :
14-16 Oct 1997
Firstpage :
586
Lastpage :
590
Abstract :
Sea clutter amplitude is often modeled as a compound random variable Z=AX, where A is a positive valued random variable and X has a Rayleigh distribution. The K and discrete Rayleigh mixture distributions arise from this model using a gamma or discrete distribution, respectively, for A. In certain applications, successive values of A may be correlated. If this correlation is modeled as a finite Markov process, Z is described by a hidden Markov model (HMM). Amplitude only and phase coherent detection statistics are derived from the HMM models using locally optimal and likelihood ratio techniques, respectively. The performance of these algorithms are compared with CFAR and Doppler processors using radar data
Keywords :
radar clutter; CFAR; Doppler processors; HMM; K distribution; Rayleigh distribution; algorithms; amplitude detection statistics; compound random variable; correlation; discrete Rayleigh mixture distribution; discrete distribution; finite Markov process; gamma distribution; hidden Markov models; likelihood ratio techniques; locally optimal techniques; performance; phase coherent detection statistics; positive valued random variable; radar data; radar detection; sea clutter amplitude;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Radar 97 (Conf. Publ. No. 449)
Conference_Location :
Edinburgh
ISSN :
0537-9989
Print_ISBN :
0-85296-698-9
Type :
conf
DOI :
10.1049/cp:19971742
Filename :
629246
Link To Document :
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