Low Complexity DOA Estimation using Coprime Circular Array
Ping Li, Jianfeng Li, Changbo Ye, Xiaofei Zhang · 2020
In this paper, we propose a low complexity direction of arrival (DOA) estimation method using coprime circular array. Phase ambiguity problem arises when adjacent spacing in the array is enlarged. In contrast to sparse uniform linear array (ULA), the phase difference between adjacent elements in uniform circular array (UCA) varies, which leads to different ambiguity angles. This ambiguity can be eliminated by designing two circular subarrays with coprime radius. For DOA estimation, we utilize the cross covariance matrix (CCM) between the two-subarrays, which is then enhanced via spatial averaging. Thereafter, the improved propagator method (PM) is developed to obtain the two projection matrices, which requires neither overall covariance matrix construction nor eigenvalue decomposition. Finally, we substitute the spatial spectrum peaks of one subarray into the other one to solve the problem of ambiguity angle. Numerical simulations are performed to demonstrate the effectiveness of proposed method, in terms of both computational complexity and estimation accuracy.