DocumentCode
1385014
Title
Signal detection using the radial basis function coupled map lattice
Author
Leung, Henry ; Hennessey, Geoffrey ; Drosopoulos, Anastasios
Author_Institution
Dept. of Electr. & Comput. Eng., Calgary Univ., Alta., Canada
Volume
11
Issue
5
fYear
2000
fDate
9/1/2000 12:00:00 AM
Firstpage
1133
Lastpage
1151
Abstract
From observation sea clutter, radar echoes from a sea surface, is chaotic rather than random. We propose the use of a spatial temporal predictor to reconstruct the chaotic dynamic of sea clutter because electromagnetic wave scattering is a spatial temporal phenomenon which is physically modeled by partial differential equations. The spatial temporal predictor used here is called radial basis function coupled map lattice (RBF-CML) which uses linear combination to fuse either measurements in different spatial domains for an RBF prediction or predictions from several RBF nets operated on different spatial regions. Using real-life radar data, it is shown that the RBF-CML is an effective method to reconstruct the sea clutter dynamic. The RBF-CML predictor is then applied to detect small targets in sea clutter using the constant false alarm rate (CFAR) principle. The spatial temporal approach is shown, both theoretically and experimentally, to be superior to a conventional CFAR detector
Keywords
chaos; electromagnetic wave scattering; marine radar; prediction theory; radar clutter; radar target recognition; radial basis function networks; signal detection; RBF coupled map lattice; chaos; constant false alarm rate; marine radar; radar echoes; radar target recognition; radial basis function neural networks; sea clutter; signal detection; spatial temporal prediction; wave scattering; Chaos; Couplings; Electromagnetic modeling; Electromagnetic scattering; Partial differential equations; Predictive models; Radar clutter; Sea surface; Signal detection; Surface reconstruction;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.870045
Filename
870045
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