Literature DB >> 18249840

Signal detection using the radial basis function coupled map lattice.

H Leung1, G Hennessey, A Drosopoulos.   

Abstract

Conventional detection methods used in current marine radar systems do not perform efficiently in detecting small targets embedded in a clutter environment. Based on a recent observation that sea clutter, radar echoes from a sea surface, is chaotic rather than random, we propose using 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 a linear combiner 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.

Entities:  

Year:  2000        PMID: 18249840     DOI: 10.1109/72.870045

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw        ISSN: 1045-9227


  2 in total

1.  Cooperative recurrent modular neural networks for constrained optimization: a survey of models and applications.

Authors:  Mohamed S Kamel; Youshen Xia
Journal:  Cogn Neurodyn       Date:  2008-02-01       Impact factor: 5.082

2.  Sea clutter reduction and target enhancement by neural networks in a marine radar system.

Authors:  Raúl Vicen-Bueno; Rubén Carrasco-Álvarez; Manuel Rosa-Zurera; José Carlos Nieto-Borge
Journal:  Sensors (Basel)       Date:  2009-03-16       Impact factor: 3.576

  2 in total

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