Maximum likelihood, ESPRIT, and periodogram frequency estimation of radar signals in K-distributed clutter

The contribution of this paper is the derivation of the joint maximum likelihood (ML) estimator of complex amplitude and Doppler frequency of a radar target signal embedded in correlated non-Gaussian clutter modelled as a compound-Gaussian process. The estimation accuracy of the ML frequency estimator is investigated and compared with that of the well-known periodogram and ESPRIT estimators under various operational scenarios. The hybrid Cramer-Rao lower bound (HCRLB) and a large sample closed-form expression for the mean square estimation error are also derived for Swerling I target signal. Finally, numerical results obtained by Monte Carlo simulation are checked by means of measured sea clutter data for the general case of fluctuating target amplitude. (C) 2000 Elsevier Science B.V. All rights reserved.