Statistical Analysis of a High-Resolution Sea-Clutter Database

This paper presents the statistical analysis of an experimental high-resolution sea-clutter database, collected with a high-resolution Ka-band radar at the south coast of Spain. The main motivation of this paper has been to check the validity of the available theoretical models for high-resolution sea-clutter against data corresponding to a range resolution of centimeters. The overall amplitude probability density function (pdf), the compatibility with a compound representation, and the average spectral behavior of the data are analyzed in detail. Results clearly show the suitability of the compound Gaussian model and, more precisely, that the empirical pdf is well modeled by the generalized K distribution with log-normal texture. A close agreement has also been found between the estimated clutter spectral density and a power-law model.

[1]  Donald D. Weiner,et al.  Non-Gaussian clutter modeling with generalized spherically invariant random vectors , 1996, IEEE Trans. Signal Process..

[2]  D.R. Moran,et al.  CWLFM millimeter-wave radar for ISAR imaging with range coverage , 2005, IEEE International Radar Conference, 2005..

[3]  S. Haykin,et al.  Canadian East Coast radar trials and the K-distribution , 1991 .

[4]  Anil K. Bera,et al.  Efficient tests for normality, homoscedasticity and serial independence of regression residuals , 1980 .

[5]  K. Ward Compound representation of high resolution sea clutter , 1980 .

[6]  E. Jakeman,et al.  A model for non-Rayleigh sea echo , 1976 .

[7]  Fulvio Gini,et al.  Statistical analysis of measured polarimetric clutter data at different range resolutions , 2006 .

[8]  A. Maio,et al.  Statistical analysis of real clutter at different range resolutions , 2004, IEEE Transactions on Aerospace and Electronic Systems.

[9]  S. Watts,et al.  Radar Detection Prediction in K-Distributed Sea Clutter and Thermal Noise , 1987, IEEE Transactions on Aerospace and Electronic Systems.

[10]  Marco Diani,et al.  Performance analysis of two adaptive radar detectors against non-Gaussian real sea clutter data , 2000, IEEE Trans. Aerosp. Electron. Syst..

[11]  Giuseppe Ricci,et al.  GLRT-based adaptive detection algorithms for range-spread targets , 2001, IEEE Trans. Signal Process..

[12]  E. Conte,et al.  Characterization of radar clutter as a spherically invariant random process , 1987 .

[13]  Giuseppe Ricci,et al.  A procedure for measuring the coherence length of the sea texture , 1996 .

[14]  Simon Haykin,et al.  Uncovering nonlinear dynamics-the case study of sea clutter , 2002, Proc. IEEE.

[15]  Jakov V. Toporkov,et al.  Statistical Properties of Low-Grazing Range-Resolved Sea Surface Backscatter Generated Through Two-Dimensional Direct Numerical Simulations , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[16]  C. Baker,et al.  Maritime surveillance radar Part 1 : Radar scattering from the ocean surface , 1990 .

[17]  F. Posner,et al.  Spiky sea clutter at high range resolutions and very low grazing angles , 2002 .

[18]  F. Gini,et al.  X-band sea-clutter nonstationarity: influence of long waves , 2004, IEEE Journal of Oceanic Engineering.

[19]  Muralidhar Rangaswamy,et al.  Computer generation of correlated non-Gaussian radar clutter , 1995 .

[20]  G. Brown,et al.  Guest Editorial - Special Issue On Low-grazing-angle Backscatter From Rough Surfaces , 1998 .

[21]  Fulvio Gini,et al.  High resolution sea clutter data: statistical analysis of recorded live data , 1997 .

[22]  Simon Haykin,et al.  A coherent dual-polarized radar for studying the ocean environment , 1991, IEEE Trans. Geosci. Remote. Sens..

[23]  J. D. Barter,et al.  Lineshape analysis of breaking-wave Doppler spectra , 1998 .

[24]  Joel Goldman,et al.  Detection in the presence of spherically symmetric random vectors , 1976, IEEE Trans. Inf. Theory.

[25]  J. Wright A new model for sea clutter , 1968 .

[26]  C. Baker,et al.  Maritime surveillance radar. II. Detection performance prediction in sea clutter , 1990 .

[27]  G. Lampropoulos,et al.  High resolution radar clutter statistics , 1999 .

[28]  A. Farina,et al.  Improvement factor for real sea-clutter Doppler frequency spectra , 1996 .

[29]  Georgios B. Giannakis,et al.  Time-averaged subspace methods for radar clutter texture retrieval , 2001, IEEE Trans. Signal Process..

[30]  Bernie Mulgrew,et al.  Re-examining the nature of radar sea clutter , 2002 .

[31]  F. Gini,et al.  Texture modelling, estimation and validation using measured sea clutter data , 2002 .

[32]  Marco Lops,et al.  Canonical detection in spherically invariant noise , 1995, IEEE Trans. Commun..

[33]  A. Asensio-Lopez,et al.  Application of the Radon transform to detect small-targets in sea clutter , 2009 .

[34]  R. Garello,et al.  GLRT subspace detection for range and Doppler distributed targets , 2008, IEEE Transactions on Aerospace and Electronic Systems.

[35]  C. Galdi,et al.  Random walk based characterisation of radar backscatter from the sea surface , 1998 .

[36]  Harm Greidanus,et al.  Analysis of sea spikes in radar sea clutter data , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[37]  Fulvio Gini,et al.  Statistical Analysis of High-Resolution SAR Ground Clutter Data , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[38]  A. Asensio-Lopez,et al.  High range-resolution radar scheme for imaging with tunable distance limits , 2004 .

[39]  Marco Lops,et al.  Modelling and simulation of non-Rayleigh radar clutter , 1991 .

[40]  A. Farina,et al.  Impact of clutter spectra on radar performance prediction , 2001 .

[41]  Marco Lops,et al.  Fitting the exogenous model to measured data , 1993, 1993 IEEE Instrumentation and Measurement Technology Conference.