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
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