Evaluation and performance comparison of detection algorithms in a maritime environment

In this paper, a framework will be proposed for the evaluation of detector algorithms in a maritime environment. Performance metrics and test cases will be defined to allow the impartial comparison of different detectors. In this framework the main approaches for detector comparison are numerical simulation and the use of recorded sea clutter and boat reflectivity data. Available data suitable to the fair comparison of different algorithms will be highlighted, with results for a selection of algorithms. The proposed framework, performance metrics and baseline cases give researchers and system engineers the ability to quantify system performance in a complex clutter environment and to evaluate the effectiveness of a particular detector (or radar design(s)) as compared to another.

[1]  C. J. Baker,et al.  A statistical model for radar target detection in clutter , 1988, Proceedings of the 1988 IEEE National Radar Conference.

[2]  K. Ward,et al.  Sea clutter: Scattering, the K distribution and radar performance , 2007 .

[3]  Fulvio Gini,et al.  Covariance matrix estimation for CFAR detection in correlated heavy tailed clutter , 2002, Signal Process..

[4]  J. Cilliers,et al.  DataWare: Sea Clutter and Small Boat Radar Reflectivity Databases [Best of the Web] , 2010, IEEE Signal Processing Magazine.

[5]  G. Davidson.  Simulation of coherent sea clutter , 2010 .

[6]  Brian Clement Armstrong.  Processing techniques for improved radar detection in spiky clutter , 1992 .

[7]  Simon Watts,et al.  Use of sea clutter models in radar design and development , 2010 .

[8]  C. Baker,et al.  Analysis of calibrated sea clutter and boat reflectivity data at C- and X-band in South African coastal waters , 2007 .

[9]  L.E. Brennan,et al.  Theory of Adaptive Radar , 1973, IEEE Transactions on Aerospace and Electronic Systems.

[10]  F. Gini,et al.  Impact of Sea Clutter Nonstationarity on Disturbance Covariance Matrix Estimation and CFAR Detector Performance , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[11]  P.L. Herselman,et al.  Improved covariance matrix estimation in spectrally inhomogeneous sea clutter with application to adaptive small boat detection , 2008, 2008 International Conference on Radar.

[12]  Guo Lixin,et al.  Modification of Classical SPM for Slightly Rough Surface Scattering with Low Grazing Angle Incidence , 2005 .

[13]  K. Ward,et al.  The correlation properties of gamma and other non-Gaussian processes generated by memoryless nonlinear transformation , 1999 .

[14]  James P. Reilly,et al.  Radar design principles - Signal processing and the environment (2nd revised and enlarged edition) , 1991 .

[15]  A. Farina,et al.  Vector subspace detection in compound-Gaussian clutter. Part I: survey and new results , 2002 .

[16]  Fulvio Gini,et al.  A cumulant-based adaptive technique for coherent radar detection in a mixture of K-distributed clutter and Gaussian disturbance , 1997, IEEE Trans. Signal Process..

[17]  A. Farina,et al.  Selected list of references on radar signal processing , 2001 .