Statistics of SAR Interferograms with Application to Moving Target Detection

Abstract : This report examines the statistics of the phase and magnitude of SAR interferograms towards the deployment of along-track interferometry (ATI) for slow ground moving target indication (GMTI). Great importance is attached to the practical applicability of the derived theoretical results, particularly with regard to the experimental MTI-mode of Radarsat2. Therefore, the results are evaluated with experimental airborne SAR data acquired during flight trials conducted in Petawawa in 1999. While the known probability density function (pdf) of the interferogram's phase (derived under the assumption of Gaussian backscatter) is shown to agree almost perfectly for a wide variety of backscatter conditions, the corresponding magnitude's pdf tends to deviate strongly in most cases. Motivated by this discrepancy, a novel distribution is derived for the interferogram's magnitude. This pdf, called the polynomial or p-distribution, matches the real data much more accurately, particularly for extremely heterogeneous composite terrain. Based on these statistics, a completely automatic detection scheme with constant false alarm rates for slow moving targets is proposed. All involved parameters required to determine the detection thresholds are estimated from the sample data. It is demonstrated on the basis of a real SAR scene that this detector is capable of detecting slow moving vehicles within severe ground clutter. Finally, practical aspects of the implementation and numerical stability are addressed, since many of the functions involved are comprised of indefinite power series which have to be handled cautiously.

[1]  N. R. Goodman Statistical analysis based on a certain multivariate complex Gaussian distribution , 1963 .

[2]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[3]  J. Goodman Some fundamental properties of speckle , 1976 .

[4]  M Tur,et al.  When is speckle noise multiplicative? , 1982, Applied optics.

[5]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[6]  E. Jakeman,et al.  Generalized K distribution: a statistical model for weak scattering , 1987 .

[7]  Leslie M. Novak,et al.  Studies of target detection algorithms that use polarimetric radar data , 1988 .

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

[9]  R. Bamler,et al.  Phase statistics of interferograms with applications to synthetic aperture radar. , 1994, Applied optics.

[10]  Jong-Sen Lee,et al.  Intensity and phase statistics of multilook polarimetric and interferometric SAR imagery , 1994, IEEE Trans. Geosci. Remote. Sens..

[11]  L. Joughin,et al.  Effective number of looks for a multilook interferometric phase distribution , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[12]  M. Seymour,et al.  Maximum likelihood estimation for SAR interferometry , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[13]  Allen R. Miller,et al.  Statistics of phase difference and product magnitude of multi-look processed Gaussian signals , 1994 .

[14]  Donald B. Percival,et al.  Probability density functions for multilook polarimetric signatures , 1994, IEEE Trans. Geosci. Remote. Sens..

[15]  Lars M. H. Ulander,et al.  Repeat-pass SAR interferometry over forested terrain , 1995, IEEE Transactions on Geoscience and Remote Sensing.

[16]  Ridha Touzi,et al.  Statistics of the Stokes parameters and of the complex coherence parameters in one-look and multilook speckle fields , 1996, IEEE Trans. Geosci. Remote. Sens..

[17]  Corina da Costa Freitas,et al.  A model for extremely heterogeneous clutter , 1997, IEEE Trans. Geosci. Remote. Sens..

[18]  Mehrdad Soumekh,et al.  Synthetic Aperture Radar Signal Processing with MATLAB Algorithms , 1999 .

[19]  Riccardo Lanari,et al.  Synthetic Aperture Radar Processing , 1999 .

[20]  Paris W. Vachon,et al.  Coherence estimation for SAR imagery , 1999, IEEE Trans. Geosci. Remote. Sens..