Unimodular Waveform Design With Desired Ambiguity Function for Cognitive Radar

Abstract

In this correspondence, we target the problem of radar waveform design based on the ambiguity function. The problem is formulated as an optimization, where the nonconvex unimodularity constraint is also considered. The problem is solved by successive application of majorization minimization (MM) and projected gradient descent algorithm (PGD). The proposed method has the unprecedented ability to synthesize nonzero subregions. The superiority of the proposed algorithm in achieving zero subregions is confirmed through simulation, where a suppression superiority of at least 6 dB is evident compared to the best state-of-the-art benchmark.