Radar clutter classification using autoregressive modelling, K-distribution and neural network

This paper is concerned with the classification of radar returns including sea, ground and composite clutters. We first present an analysis of radar clutter recorded data allowing to validate the K amplitude distribution and the autoregressive modelling of the spectrum. Then, we briefly describe a classifier based on a multi-layer neural network. The inputs of which are the shape parameter of the K-distribution, the magnitude and the phase of the poles and the reflection coefficients calculated by means of the Burg´s or multi-segment algorithm. Experimental results are presented to illustrate the performance of the proposed classifier