混合缺陷部分校准阵列的测向

IF 4.6 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Yihan Su;Lei Wang;Zhiyong Hu;Yimin Liu
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引用次数: 0

摘要

近年来,部分校准阵列的测向受到了广泛的关注。从校准缺陷的角度来看,现有文献主要关注子阵间位移,而对子阵倾角的讨论相对有限。本文介绍了一个综合信号模型,该模型考虑了混合缺陷,包括子阵间位移、增益/相位不确定性,特别是子阵倾角。在此基础上,我们提出了一种基于块结构转向矩阵恢复的无网格两阶段测向方法,称为BSSMR。首先,我们利用测量的协方差矩阵来恢复转向矩阵,然后基于块结构阵列流形估计到达方向(DOA)。给出了BSSMR的一个充分条件,并对其渐近收敛性进行了分析。仿真结果表明,该方法在混合缺陷情况下具有较好的鲁棒性,达到了cram - rao下界(CRLB)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Direction Finding in Partly Calibrated Arrays With Hybrid Imperfections
Direction finding in partly calibrated arrays has received significant attention in recent years. From the perspective of the calibration imperfections, existing literature predominantly focuses on inter-subarray displacement, while there has been relatively limited discussion regarding subarray inclination. This article introduces a comprehensive signal model that accounts for hybrid imperfections, including inter-subarray displacement, gain/phase uncertainty, and particularly subarray inclination. Building on this, we propose a gridless two-stage method based on block-structured steering matrix recovery for direction finding, termed BSSMR. Initially, we leverage the covariance matrix of the measurements to recover the steering matrix, followed by the estimation of direction-of-arrivals (DOA) based on the block-structured array manifold. We provide a sufficient condition for BSSMR and conduct an analysis of its asymptotic convergence behavior. Numerical simulations demonstrate the robust performance of our proposed method in scenarios of hybrid imperfections, which reaches the Cramér-Rao lower bound (CRLB).
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来源期刊
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing 工程技术-工程:电子与电气
CiteScore
11.20
自引率
9.30%
发文量
310
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.
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