Sparse Sensing for MIMO Array Radar

Multi-Input Multi-Output (MIMO) array radar is a new type of radar system that adopts waveform diversity technology at the transmitter. In essence, different transmit antennas can transmit differed orthogonal or partially correlated signals. In this regard, MIMO radar offers more degrees of freedom (DoFs) compared with the phased array counterparts. This provides opportunities for improved radar functions, such as target detection, beamforming and direction of arrival (DOA) estimation. In the previous chapters, sparse receiver array design was delineated, which enhances the radar performance by fully utilizing the spatial DoFs and reduce hardware cost. Recently, with the increased demands of cost saving and improved performance, the optimization of sparse transceiver for MIMO radar has become particularly important. In this chapter, we examine the sparse optimization of MIMO radar transceiver for different tasks. In Sect. 6.1, we briefly introduce the principle of MIMO array transceiver and review the state of the art in sparse array design. In Sect. 6.2, the sparse MIMO array transceiver design for enhanced adaptive beamforming is presented under the assumption of known environmental conditions. We examine the active sparse array design enabling the maximum signal to interference plus noise ratio (MaxSINR) beamforming at the MIMO radar receiver through successive convex approximation (SCA) incorporating the two dimensional group sparsity promoting regularization. In Sect. 6.3, the cognitive-driven optimization of sparse array transceiver for MIMO radar beamforming is introduced, which further eliminates the prerequisite of prior information. We propose a cognitive-driven MIMO array design where both the beamforming weights and the transceiver configuration are adaptively and concurrently optimized in dynamic operating environment via a “perception-action” cycle. Finally, concluding remarks are provided in Sect. 6.4.