Artificial Neural Network-Based Clutter Reduction Systems for Ship Size Estimation in Maritime Radars
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Research Article Artificial Neural Network-Based Clutter Reduction Systems for Ship Size Estimation in Maritime Radars ´ R. Vicen-Bueno, R. Carrasco-Alvarez, M. Rosa-Zurera (EURASIP Member), J. C. Nieto-Borge, and M. P. Jarabo-Amores Signal Theory and Communications Department, Superior Politechnic School, University of Alcal´a, Alcal´a de Henares, 28805 Madrid, Spain Correspondence should be addressed to R. Vicen-Bueno, [email protected] Received 1 July 2009; Revised 16 November 2009; Accepted 14 January 2010 Academic Editor: Frank Ehlers Copyright © 2010 R. Vicen-Bueno et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The existence of clutter in maritime radars deteriorates the estimation of some physical parameters of the objects detected over the sea surface. For that reason, maritime radars should incorporate efficient clutter reduction techniques. Due to the intrinsic nonlinear dynamic of sea clutter, nonlinear signal processing is needed, what can be achieved by artificial neural networks (ANNs). In this paper, an estimation of the ship size using an ANN-based clutter reduction system followed by a fixed threshold is proposed. High clutter reduction rates are achieved using 1-dimensional (horizontal or vertical) integration modes, although inaccurate ship width estimations are achieved. These estimations are improved using a 2-dimensional (rhombus) integration mode. The proposed system is compared with a CA-CFAR system, denoting a great performance improvement and a great robustness against changes in sea clutter conditions and ship parameters, independently of the direction of movement of the ocean waves and ships.
1. Introduction The measurement of physical parameters of the sea surface by radar systems plays an important role in ocean surveillance and remote sensing. Depending on the application, two different points of view can be identified. From the first one, sea measurements contain useful information about the ocean surface. The characterization of the nonlinear dynamic of sea waves becomes the focal point of the study. From the second one, if the primary objective is the detection of objects over the sea surface, such as ships and/or boats, and the posterior estimation of their physical parameters, the information about the sea surface is referred as sea clutter and viewed as an interference to suppress. The studies presented in this paper are focused on the last case, where the separation of sea clutter and ship information allows the estimation of ship physical parameters. Maritime radar systems usually only measure the intensity of the returned electromagnetic echo (incoherent measurement). This kind of systems is commonly used, for instance, in maritime traffic control centers. They are con-
sidered to estimate some ship physical parameters in our studies. Among other final applications, one part of our proposal, the clutter red
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