DoA estimation based on accelerated structured alternating projection using coprime array
Yuqi Zhang, Shengheng Liu, Zihuan Mao, Yongming Huang · Seventh Asia Pacific Conference on Optics Manufacture (APCOM 2021) · 2022
In this paper, we address the problem of direction finding using coprime array, which is one of the most preferred sparse array configurations in the radar community. Motivated by the fact that conventional algorithms based on the convex relaxation is computationally expensive, we propose a non-convex accelerated structured alternating projection-based direction-of-arrival (DoA) estimation approach without the need to solve a semi-definite programming. The low rank Hankel matrices constructed by the sub-arrays of the virtual uniform linear array (ULA) and the sparse hole signal respectively correspond to the sets of low-rank matrices and sparse manifolds. After initialization, we update the estimations by iterative projections between the two sets, which employs an accelerated low-rank approximation method. Once the desired Hankel matrix with DoA information is recovered, simple subspace-based spectral estimation algorithms can be applied to obtain the target directions. The estimation performance in terms of root-mean-square error is examined and the superiority of the proposed method over the competitive approaches in the computational cost sense is also demonstrated.