Self-calibration algorithm with gain-phase errors array for robust doa estimation

被引：0

作者：

Wei Z. ^{[1
]}

Wang W. ^{[1
]}

Dong F. ^{[1
]}

Liu P. ^{[1
]}

机构：

[1] College of Intelligent System Science and Engineering, Harbin Engineering University, Harbin, 150001, Heilongjiang

来源：

Progress In Electromagnetics Research M | 2020年 / 99卷

基金：

中国国家自然科学基金;

关键词：

Uncertainty analysis - Calibration - Cramer-Rao bounds - Iterative methods - Optimization;

D O I：

10.2528/pierm20090701

中图分类号：

学科分类号：

摘要：

The performance of direction-of-arrival (DOA) estimation algorithms degrades when a partly calibrated array is adopted due to the existing unknown gain-phase uncertainties. In addition, the spatial discretized searching grid also limits the performance improvement and effectiveness of subspace-based DOA estimation algorithms, especially when the true angles do not lie on the grid points which is referred to the off-grid problem alike. In this paper, a self-calibration DOA estimation algorithm is proposed which solves the array calibration and off-grid problems simultaneously. Firstly, the signal model for a partly calibrated array with gain-phase uncertainties is established. To suppress the off-grid errors, an optimization problem for joint parameters estimation is constructed by substituting the approximation of the steering vector into a newly constructed objective function. The alternative minimization (AM) algorithm is employed to calculate the joint DOA and gain-phase uncertainty estimations. Within each iteration step of the optimization problem, a closed-form solution is derived that guarantees the convergence of the proposed algorithm. Furthermore, the Cramér-Rao bound (CRB) for the partly calibrated arrays with unknown gain-phase uncertainties is also derived and analyzed in the paper. Simulation results demonstrate the effectiveness of the proposed algorithm. © 2020, Electromagnetics Academy. All rights reserved.

引用

页码：1 / 12

页数：11