Linear prediction approach to Doppler estimation of radar signals in the presence of ground clutter

Abstract

Linear-prediction-based methods are applied to mean Doppler estimation of radar signals in the presence of ground clutter when only a small number of samples is available for processing. The authors show the ability of these methods to resolve weather signals from ground clutter in unfavourable conditions, i.e. when the clutter is stronger and its spectrum is narrower than the signal's. It is shown that the Prony method can be applied to this task. In addition, given the a priori information about ground clutter, the Prony method can be simplified to derive a convenient formula for mean Doppler frequency estimation in the presence of ground clutter. This estimator can be considered as a generalization of the pulse-pair (PP) estimator. Such a scheme can give satisfactory results in resolving weather signals from ground clutter for signal-to-noise ratios (SNR) above 20 dB. The eigendecomposition-based minimum-norm method is applied to lower the SNR threshold to 10 dB. The methods are compared with combinations of various ground clutter filters and the PP estimator. >