Transmit beamforming for DOA estimation based on Cramer-Rao bound optimization in subarray MIMO radar

摘要

Compared to conventional phased-array radar, M1MO radar benefiting from its extra degrees of freedom brought by waveform diversity allows to optimize the Cramer-Rao Bound (CRB) for Direction-of-arrival (DOA) estimation more freely. In this paper, under the premise that the general angular directions of targets are known as priori, a new transmit beamforming method for subarray MIMO radar is proposed with the application to improve the performance of DOA estimator for multiple targets. The CRB expression for DOA estimation of subarray MIMO radar is derived firstly. Then, the correlation matrix of the transmitted waveforms is optimized to minimize the CRB for DOA estimation. Once the optimized correlation matrix is determined, eigendecomposition method is applied to calculate the subarray beamforming weights. Meanwhile, fewer orthogonal waveforms are transmitted in the proposed method compared to conventional MIMO radar, which means that less number of subarrays will be used. The reduction in the number of transmitted orthogonal waveforms can effectively reduce the computational complexity. The proposed method obtains the optimized tradeoff between the effective aperture of virtual array and coherent gain, and consequently improves the performance of DOA estimator. Simulation results show that the proposed method has a superior performance comoared with the existing methods.