Multispectrally Constrained Waveform Design for MIMO Radar Direction Finding

Abstract

This paper focuses on the design of transmit waveforms for multiple-input-multiple-output (MIMO) radar systems in a spectrally crowded environment. The purpose is to improve the angle estimation performance of MIMO radar by minimising the asymptotic estimation bound of multiple signal classification (MUSIC) algorithm. To enhance the spectrum coexistence capabilities of radar system, a multispectral constraint is imposed on the sought waveforms. Moreover, a peak-to-average-power ratio (PAPR) constraint is enforced on the radar waveform to improve the practicability. To tackle the encountered nonconvex optimisation problem, a cyclic algorithm based on optimal covariance matrix matching (OCMM) and alternating direction method of multipliers (ADMM) are developed. The proposed algorithm first transforms the established optimisation problem into an OCMM optimisation problem with a more tractable structure, followed by the adoption of the ADMM method to obtain high-quality solution. Numerical examples are provided to show that the proposed algorithm can efficiently design the transmit waveforms, further improving the target localisation accuracy and enhancing the spectrum compatibility of the radar system.