DOA and Doppler Frequency Estimation Based on Sub-aperture MUSIC

Most available algorithms for DOA estimation in monostatic MIMO radar involve the computation of covariance matrix and its inversion or eigendecomposition, of which the computational complexity is expensive, especially in the case that both the number of sensors and snapshots are large. To solve this problem, a high-resolution algorithm for joint direction-of-arrival (DOA) and Doppler Frequency estimation based on sub-aperture MUSIC in monostatic MIMO radar is presented. Firstly, the received data matrix form each transmitter is evenly divided into four sub-blocks. Then two-dimensional fast Fourier transforms (2D-FFTs) is applied to each sub-block in order to achieve coherent integration. By utilizing the data corresponding to the peaks of coherent integration in each sub-block, a reduced-dimensional data vector is constructed for joint DOA and Doppler frequency estimation via root-MUSIC. Since the full-dimensional covariance matrix estimation and eigendecomposition are avoided, the computational complexity is relatively small. Simulation results demonstrate the effectiveness of the proposed method with slightly better performance than that of ESPRIT-based method.