Joint transmit filter and sparse array design with transmit subaperturing FDA-MIMO radar

Increasingly complex electromagnetic environment makes some troubles for a radar system. Improving the performance of the radar detection and suppressing the interferences are important challenges. In this study, joint transmit filters and sparse array design enabling the maximum signal to interference plus the noise ratio (SINR) beamforming at the transmit subaperturing frequency diverse array multiple-input multiple-output (TS-FDA-MIMO) radar is examined. However, the optimisation problem is non-convex. A cycle iteration algorithm is proposed to obtain the optimal transmit filters and sparse array. The total problem is divided into two sub-problems. The first optimisation sub-problem is the sparse design and the Successive Convex Approximation (SCA) with two-dimensional reweighted mixed l1, 2-norm method is introduced to solve the sub-problem. In addition, the transmit filters design is the second optimisation problem. The sub-problem is changed to the semi-definite relaxation (SDR) problem and the Gaussian random method is utilised to obtain the optimal transmit filters. Through the cycle iteration of the two sub-problems, the optimal solutions are obtained. Finally, the simulation results verified the effectiveness of the proposed method.