An adaptive solution for the detection of small and slowly-moving targets in highly ambiguous radar context

This paper deals with the detection problem of small and slowly-moving targets in the context of highly ambiguous pulse Doppler radar using a medium Pulse Repetition Frequency (PRF). A solution for exploiting multiple-burst signals of these radars is proposed. It combines a fast iterative Maximum Likelihood (ML) estimator for target parameter estimation and ambiguities solving and an adaptive detector that uses a multiple-bursts Clutter Correlation Matrix (CCM) estimator to increase the number of Training Data (TD). Simulation results show that the proposed approach allows to resolve ambiguities and reveals the presence of small targets buried into strong ground clutter response.