Slow-Time Ambiguity Function Shaping With Spectral Coexistence for Cognitive Radar

Abstract

In the spectrum-congested environment, weak target obscuration can be addressed by simultaneously shaping the ambiguity function and waveform spectrum based on cognitive radar a priori information. In this paper, we investigate joint waveform design to suppress slow-time ambiguity function (STAF) disturbance power and overlapping frequency band energy. Thus, a novel design criterion involving minimizing the interested range-Doppler blocks of STAF and energy spectrum density (ESD) stopband is constructed, which subject to the waveform energy and peak-to-average ratio (PAR) constraints. To cope with the resulting complex quartic optimization problem, a waveform design approach is proposed which utilizes the iterative sequential quartic optimization (ISQO) algorithm framework to obtain a closed-form solution at each iteration. Finally, the designed waveforms can suppress the interested range-Doppler block level while satisfying the spectral coexistence requirements. Numerical simulation results verify that the proposed method has higher STAF disturbance suppression performance than stateof-the-art methods. Meanwhile, this method also possesses the ability to reject narrow-band spectrum interference.