Waveform Design for MIMO DFRC Systems: Finer Sensing and Safer Communications

Abstract

This paper considers the design of constant-envelope waveforms for multiple-input-multiple-output (MIMO) dual-function radar communication (DFRC) systems. The purpose is to improve the angle estimation performance of the multiple signal classification (MUSIC) algorithm through minimizing its asymptotic estimation error bound. To guarantee the communication performance, we enforce an energy constraint as well as a cosine similarity-based constraint on the synthesized communication signals. Additionally, we constrain the energy transmitted toward each potential eavesdropper to a low level, which prevents the waveforms from being intercepted. To tackle the encountered non-convex optimization problem, we develop two iterative algorithms. The first algorithm is based on the minorization-maximization method, wherein we construct a quadratic surrogate to minorize the approximate objective function. Then we use the alternating direction method of multipliers (ADMM) to tackle the quadratic programming problem. In the second algorithm, we directly tackle the waveform design problem by the ADMM method. Numerical examples are provided to show that through elaborate waveform design, the MIMO DFRC system is capable to realize high-performance target localization and covert communications simultaneously.