Frequency estimation of radar/sonar signals against correlated non-Gaussian noise

The contribution of this work is the derivation of the joint maximum likelihood estimator (MLE) of complex amplitude and Doppler frequency of a radar/sonar target signal embedded in correlated non-Gaussian noise modeled 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 Cramér-Rao lower bound (HCRLB) and a large sample closed-form expression for the mean square estimation error (mse) 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.