Optimum parameter estimate for K-distributed clutter using multiple moments

Mohammed Jahangir; David Blacknell

doi:10.1117/12.262723

17 December 1996 Optimum parameter estimate for K-distributed clutter using multiple moments

Mohammed Jahangir, David Blacknell

Proceedings Volume 2958, Microwave Sensing and Synthetic Aperture Radar; (1996) https://doi.org/10.1117/12.262723
Event: Satellite Remote Sensing III, 1996, Taormina, Italy

Abstract

The authors analyze the sub-optimal performance of simple texture measures for estimating the reciprocal order parameter of K-distributed radar clutter. A non-committal neural net has been applied to the parameter estimation task which has shown that improved error estimates are obtained when multiple moments are used to characterize the texture. Prompted by this result a new estimator is proposed which combines the mean normalized log intensity and the amplitude contrast moments of the imaged data. Its error performance is determined by the relative weighting in which the two moments are combined. With an appropriate choice of the weighting the modified estimator outperforms the normalized log estimator and gives close to maximum likelihood performance on the estimates over a wide range of the parameters values which are of interest.

Citation Download Citation

Mohammed Jahangir and David Blacknell "Optimum parameter estimate for K-distributed clutter using multiple moments", Proc. SPIE 2958, Microwave Sensing and Synthetic Aperture Radar, (17 December 1996); https://doi.org/10.1117/12.262723

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