A Fast and Robust DOA Estimation Method Based on JSVD for Co-Prime Array

Compared with the uniform linear array, the co-prime array can obtain a large array aperture with fewer array elements, which is good to improve the accuracy of direction-of-arrival (DOA) estimation. However, most of existing DOA estimation methods is not suitable for co-prime array because of high computational complexity and low adaptability. Therefore, a fast and robust DOA estimation method for the co-prime array based on the joint singular value decomposition (JSVD) is proposed in this paper. In the proposed method, the co-prime array is equivalently divided into two uniform sparse linear subarrays according to the definition of co-prime array geometry firstly. Then, utilizing the JSVD algorithm and the periodic repeatability of uniform sparse linear array, two series of DOAs, including ambiguity angles can be obtained individually by each subarray. By analysis of these two series of DOAs, the correct DOAs can be obtained based on the coprime property of two equivalent uniform sparse linear subarrays of the co-prime array. The spectral search is not required in the proposed method, so that the computational complexity is lower relative to the MUSIC-based DOA estimation methods. Moreover, the angle pairing is achieved automatically in JSVD processing, thus the adaptability of proposed method is better than the traditional DOA estimation methods. Finally, the performance and advantages of proposed method are verified by numerical simulations.