Low computation 2-D imaging for MIMO sonar based on sparse array technology

To reduce the computation burden of multiple-input multiple-output (MIMO) sonar imaging system, a low computational imaging approach based on sparse array technology is proposed in this paper. Specifically, considering the MIMO sonar with a virtual rectangular planar array, we adopt the simulated annealing (SA) algorithm to optimize the layout and weight coefficients of the virtual array into a sparse one. Then, according to the one-to-one relationship between a matched filter and a virtual sensor, the matched filters whose corresponding virtual elements are inactive in the virtual array are also removed. Finally, the outputs of remaining matched filters are collected as the inputs of beamformers and the 2-D imaging result is obtained with further processing. Since the sensor number in the sparse virtual array is much smaller than that of the original filled virtual one, the number of matched filters in the MIMO sonar imaging system is greatly reduced and hence, the computation burden is significantly simplified. Numerical simulations are provided for demonstrating the effectiveness of our approach.