Clutter Parameter Estimation Based on Indirect Algorithms

Abstract

Indirect algorithms for clutter parameter estimation using linear transformations of initial data have been synthesized by the maximum likelihood method. The likelihood function was introduced for the input samples transformed in accordance with the sum-difference algorithms. The estimation algorithms of the interperiod correlation and Doppler phase shift coefficients derived by solving the appropriate likelihood equations do not contain the traditional complex multiplication operation over input data. The functional block diagram of the estimator of appropriate clutter parameters that can be used in adaptive rejection filters is presented. The estimation accuracy analysis of required parameters of clutter is performed depending on the size of training sample and correlation properties of clutter. The comparison of simulation and calculation results for indirect and direct algorithms revealed their complete match and confirmed the asymptotic efficiency of resultant estimates and the equivalence of indirect and direct algorithms.