Enhanced DOD and DOA estimations in coprime MIMO radar: Modified matrix pencil method

IF 3 3区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Digital Signal Processing Pub Date : 2025-04-01 Epub Date: 2025-01-09 DOI:10.1016/j.dsp.2024.104977
Mushtaq Ahmad , Xiaofei Zhang , Farman Ali , Xin Lai
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Abstract

Recent research indicates that coprime multiple-input multiple-output (MIMO) radar systems enhance target detection and parameter estimation capabilities due to their unique array configurations. However, despite these advantages, effectively managing scenarios with both coherent and uncorrelated targets requires a delicate balance between computational efficiency and performance accuracy. In this paper, we propose an innovative approach for the joint estimation of the direction of departure (DOD) and direction of arrival (DOA) in coprime MIMO radar systems capable of effectively handling both coherent and uncorrelated targets. We first construct an extended virtual uniform rectangular array (URA) by employing array interpolation, which enhances the system's resolution capabilities. Next, we apply a low-rank structured matrix recovery technique to tackle inherent rank deficiency issues in coherent targets. This approach allows us to estimate the parameters of these targets accurately. We use the full-rank covariance matrix to directly apply the modified matrix pencil (MMP) method for estimating DOD and DOA. This dual-faceted approach automatically pairs estimated parameters without separating processing paths for coherent and uncorrelated targets. Comprehensive simulations indicate the effectiveness of our proposed algorithm in managing mixed target scenarios. It achieves high estimation accuracy and resolution while maintaining computational efficiency.
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改进的同质MIMO雷达的DOD和DOA估计:改进的矩阵铅笔法
近年来的研究表明,多输入多输出(MIMO)雷达系统由于其独特的阵列结构,提高了目标探测和参数估计能力。然而,尽管有这些优点,有效地管理具有连贯和不相关目标的场景需要在计算效率和性能准确性之间取得微妙的平衡。在本文中,我们提出了一种能够有效处理相干和不相关目标的同质MIMO雷达系统中出发方向(DOD)和到达方向(DOA)联合估计的创新方法。我们首先利用阵列插值构造了一个扩展的虚拟均匀矩形阵列(URA),增强了系统的分辨率。其次,我们应用低秩结构化矩阵恢复技术来解决相干目标的固有秩不足问题。这种方法使我们能够准确地估计这些目标的参数。我们使用全秩协方差矩阵直接应用改进矩阵铅笔法(MMP)估计DOD和DOA。该方法在不分离相干和不相关目标的处理路径的情况下,自动对估计参数进行配对。综合仿真结果表明,本文提出的算法在管理混合目标场景方面是有效的。在保持计算效率的同时,实现了较高的估计精度和分辨率。
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来源期刊
Digital Signal Processing
Digital Signal Processing 工程技术-工程:电子与电气
CiteScore
5.30
自引率
17.20%
发文量
435
审稿时长
66 days
期刊介绍: Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal. The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as: • big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,
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