Robust Gridless DOA Estimation Using Coprime Array Under Nonuniform Noise
Jing Song, Lin Cao, Zongmin Zhao, Kehu Yang, Dongfeng Wang, Chong Fu · IEEE Transactions on Instrumentation and Measurement · 2025
Traditional direction-of-arrival (DOA) estimation algorithms fail to account for the impact of nonuniform noise in practical applications, leading to model mismatch and inaccurate DOA estimation. To overcome this issue, we propose a robust gridless sparse iterative estimation (RGSIE)-based DOA algorithm using coprime arrays. First, the received signal model is constructed, and adaptive reconstruction of the covariance matrix is achieved by setting the diagonal elements to their minimum values based on the characteristics of nonuniform noise. Subsequently, leveraging the sparsity of DOAs in the spatial domain, interpolation and overcomplete representation of the second-order received signals in the virtual domain are performed. A covariance fitting optimization problem is then formulated using a gridless sparse iterative estimation method, achieving high-precision DOA estimation and enhanced degrees of freedom. Furthermore, we employ an alternating projection (AP) strategy in the optimization process, effectively reducing the computational cost associated with complex iterative procedures. Numerical simulations validate the effectiveness and robustness of the proposed algorithm, and its performance is further demonstrated using real-world measurements from millimeter-wave radar sensors.