A Two-Step Process for a Cognitive Radar Waveform Design with Multipath Exploitation

In this paper, a two-step model is proposed, to design an optimal radar waveform to improve the detection of point like targets over a glistening surface. In this respect, a non adaptive waveform is first transmitted and a constrained Generalized Likelihood Ratio Test (GLRT) detector is used at the receiver, which exploits multipath returns in the range cell under test, by modelling the target echo as a superposition of the direct plus the multipath returns. Besides, the clutter returns are assumed to be compound-Gaussian. The Fixed Point Estimate (FPE) algorithm is used in order to estimate the clutter in the range cell under test through the secondary data collected from the out-of-bin cells. The clutter estimates are used to design an adaptive waveform for the next transmission, in order to suppress the clutter coming from adjacent cells. The proposed GLRT is also used at the end of the second transmission for the final decision. The performance analysis results show that the proposed algorithm increases the Signal-to-Clutter Ratio (SCR) of the received signal.