Relative Entropy-Based Waveform Optimization for Rician Target Detection With Dual-Function Radar Communication Systems

In this article, we consider waveform design for dual-function radar communication (DFRC) systems based on multiple-input–multiple-out (MIMO) arrays. To achieve better Rician target detection performance, use the relative entropy associated with formulated problem as metric. We also impose a multiuser interference (MUI) energy constraint waveforms to ensure achievable sum rate of communications. Two algorithms are presented tackle nonlinear nonconvex problem. first algorithm, derive quadratic function minorize objective function. quadratically constrained programming (QCQP) at each iteration, semidefinite relaxation (SDR) approach followed by rank-one decomposition procedure and an efficient alternating direction method multipliers (ADMM) proposed, respectively. second present novel ADMM algorithm optimization employ minorization-maximization (MM) in inner loop algorithm. Numerical results demonstrate superiority both algorithms. Moreover, can be extended synthesize peak-to-average power ratio (PAPR) waveforms, which allows radio frequency amplifier operate increased efficiency.