基于运动策略的扩展和差分共阵设计:基于CADiS阵列的非圆信号DOA估计

IF 3.6 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Xiaolong Li, Xin Lai, Xiaofei Zhang
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引用次数: 0

摘要

近年来,利用移动阵列估计到达方向(DOA)得到了广泛的关注。然而,移动阵列在非圆信号DOA估计中的应用研究仍然很少。置换子阵(CADiS)因其大孔径和低互耦特性而受到广泛关注。本文首先研究了由阵列运动产生的和共阵(SCA)的表达式。基于CADiS结构中的孔分布,提出了一种无孔运动策略。该方法有效地填充了差分阵(DCA)和差分阵(SCA)中的所有空穴,形成了无空穴和差分阵(SDCA)。此外,我们还提出了一种简化的阵列运动策略,以实现单步运动的无孔SDCA,并给出了可达到的最大均匀自由度(uDOFs)的封闭形式表达式。最后,我们在uDOFs、NC信号的DOA估计性能、角分辨率和可识别源的数量方面证明了所提出方法与其他阵列相比的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extended sum and difference coarray design via motion strategies: Enhanced DOA estimation for non-circular signals with CADiS arrays
Recently, the use of moving arrays for direction of arrival (DOA) estimation has garnered significant attention. Nevertheless, research on the application of moving arrays for DOA estimation of non-circular (NC) signals remains scarce. Coprime array with displaced subarray (CADiS) has gained considerable attention due to its large aperture and low mutual coupling characteristics. In this paper, we first investigate the expression for the sum coarray (SCA) generated by array motion. Based on the hole distribution in the CADiS configuration, we then propose a hole-free motion strategy. This method effectively fills all holes in the difference coarray (DCA) and SCA, resulting in a hole-free sum and difference coarray (SDCA). Furthermore, we propose a simplified array motion strategy to achieve hole-free SDCA with only single-step motion, and provide the closed-form expression for the maximum achievable uniform degrees of freedom (uDOFs). Finally, we demonstrate the superiority of the proposed methods in comparison to other arrays in terms of uDOFs, DOA estimation performance of NC signals, angular resolution, and the number of identifiable sources.
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来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
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