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Recent Advances in Sensor Array Signal Processing and its Applications in Future Communication and Radar

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 3059

Special Issue Editors

Prof. Dr. Xiaofei Zhang

E-Mail Website
Guest Editor
College of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: array signal processing; MIMO radar; communication signal processing
Special Issues, Collections and Topics in MDPI journals
Dr. Jianfeng Li

E-Mail Website
Guest Editor
College of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: array signal processing; direction-of-arrival estimation; source localization; multi-array system
Special Issues, Collections and Topics in MDPI journals
Dr. Wei Liu

E-Mail Website
Guest Editor
School of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UK
Interests: signal processing; sensor array signal processing; remote sensing; human computer interface; radar; sonar; wireless communications

Special Issue Information

Dear Colleagues,

There have been remarkable advancements in sensor array signal processing in recent years, fueled by the growing demand for high-performance communication and radar systems. Sensor arrays, comprising multiple spatially distributed sensors, offer unique capabilities for signal detection, estimation, and spatial processing. Recently, coprime and nested array signal processing has garnered considerable attention owing to its ability to expand the aperture, enhance the spatial resolution, increase the degrees of freedom, and mitigate the mutual coupling. These techniques have applications across diverse domains such as wireless communication, MIMO radar techniques, and satellite navigation.

This Special Issue aims to provide a comprehensive overview of the latest developments in sensor array signal processing and their applications. We expect distinguished submissions to highlight sparse array designs, array signal processing algorithms, and their diverse applications in communication and radar systems.

Potential topics include but are not limited to the following:

  • Sparse array design for high performance;
  • Multi-dimensional array signal processing;
  • Array calibration and compensation methods;
  • Array signal processing methods with sparse antenna arrays;
  • Array signal processing for wireless communications;
  • Aperture extension techniques for sparse MIMO radar;
  • Sparse MIMO radar design and direction finding algorithms;
  • Tracking moving sources;
  • Performance bounds on localization and tracking;
  • Massive MIMO for 5G/6G.

Prof. Dr. Xiaofei Zhang
Dr. Jianfeng Li
Dr. Wei Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sparse array
  • signal processing
  • antenna arrays
  • MIMO radar

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Published Papers (3 papers)

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Research

11 pages, 586 KiB  
Communication
FDA-MIMO Radar Rapid Target Localization via Reconstructed Reduce Dimension Rooting
by Cheng Wang, Zhi Zheng and Wen-Qin Wang
Sensors 2025, 25(2), 513; https://doi.org/10.3390/s25020513 - 17 Jan 2025
Viewed by 583
Abstract
Frequency diversity array–multiple-input multiple-output (FDA-MIMO) radar realizes an angle- and range-dependent system model by adopting a slight frequency offset between adjacent transmitter sensors, thereby enabling potential target localization. This paper presents FDA-MIMO radar-based rapid target localization via the reduction dimension root reconstructed multiple [...] Read more.
Frequency diversity array–multiple-input multiple-output (FDA-MIMO) radar realizes an angle- and range-dependent system model by adopting a slight frequency offset between adjacent transmitter sensors, thereby enabling potential target localization. This paper presents FDA-MIMO radar-based rapid target localization via the reduction dimension root reconstructed multiple signal classification (RDRR-MUSIC) algorithm. Firstly, we reconstruct the two-dimensional (2D)-MUSIC spatial spectrum function using the reconstructed steering vector, which involves no coupling of direction of arrival (DOA) and range. Subsequently, the 2D spectrum peaks search (SPS) is converted into one-dimensional (1D) SPS to reduce the computational complexity using a reduction dimension transformation. Finally, we conduct polynomial root finding to further eliminate computational costs, in which DOA and range can be rapidly estimated without performance degradation. The simulation results validate the effectiveness and superiority of the proposed RDRR-MUSIC algorithm over the conventional 2D-MUSIC algorithm and reduced-dimension (RD)-MUSIC algorithm. Full article
(This article belongs to the Special Issue Recent Advances in Sensor Array Signal Processing and its Applications in Future Communication and Radar)
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13 pages, 5347 KiB  
Communication
Efficient Aperture Fill Time Correction for Wideband Sparse Array Using Improved Variable Fractional Delay Filters
by Jie Gu, Min Xu, Wenjing Zhou and Mingwei Shen
Sensors 2024, 24(13), 4327; https://doi.org/10.3390/s24134327 - 3 Jul 2024
Viewed by 936
Abstract
To solve the problem of aperture fill time (AFT) for wideband sparse arrays, variable fractional delay (VFD) FIR filters are applied to eliminate linear coupling between spatial and time domains. However, the large dimensions of the filter coefficient matrix result in high system [...] Read more.
To solve the problem of aperture fill time (AFT) for wideband sparse arrays, variable fractional delay (VFD) FIR filters are applied to eliminate linear coupling between spatial and time domains. However, the large dimensions of the filter coefficient matrix result in high system complexity. To alleviate the computational burden of solving VFD filter coefficients, a novel multi–regultion minimax (MRMM) model utilizing the sparse representation technique has been presented. The error function is constrained by the introduction of L2–norm and L1–norm regularizations within the minimax criterion. The L2–norm effectively resolves the problems of overfitting and non–unique solutions that arise in the sparse optimization of traditional minimax (MM) models. Meanwhile, the use of multiple L1–norms enables the optimal design of the smallest sub–filter number and order of the VFD filter. To solve the established nonconvex model, an improved sequential–alternating direction method of multipliers (S–ADMM) algorithm for filter coefficients is proposed, which utilizes sequential alternation to iteratively update multiple soft–thresholding problems. The experimental results show that the optimized VFD filter reduces system complexity significantly and corrects AFT effectively in a wideband sparse array. Full article
(This article belongs to the Special Issue Recent Advances in Sensor Array Signal Processing and its Applications in Future Communication and Radar)
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14 pages, 856 KiB  
Communication
A Novel Generalized Nested Array MIMO Radar for DOA Estimation with Increased Degrees of Freedom and Low Mutual Coupling
by Zhongtian Yang, Zhengyang Bi, Ye Chen and Honghao Hao
Sensors 2024, 24(12), 3952; https://doi.org/10.3390/s24123952 - 18 Jun 2024
Viewed by 897
Abstract
In array signal processing, the mutual coupling among physical sensors can inevitably affect the estimation of the direction of arrival (DOA). Despite the fact that multiple-input and multiple-output (MIMO) radar can provide greater degrees of freedom (DOFs), the influence of mutual coupling is [...] Read more.
In array signal processing, the mutual coupling among physical sensors can inevitably affect the estimation of the direction of arrival (DOA). Despite the fact that multiple-input and multiple-output (MIMO) radar can provide greater degrees of freedom (DOFs), the influence of mutual coupling is largely overlooked in many current MIMO radar designs. To tackle this issue, we propose the utilization of a generalized nested array (GNA) in transmitter array and we introduce an expansion factor into the nested array in the receiver array. Thereby, a novel GNA-MIMO radar is put forward. The proposed MIMO radar offers O(N4) consecutive DOFs with N sensors and avoids the adverse effects of high mutual coupling caused by closely located sensors. Furthermore, we derive the closed-form expressions for the position of physical sensors and the attainable consecutive DOFs of the proposed MIMO radar. Through simulation experiments, we demonstrate the superior accuracy of the proposed MIMO configuration in DOA estimation and angle resolution under the condition of mutual coupling effect. Full article
(This article belongs to the Special Issue Recent Advances in Sensor Array Signal Processing and its Applications in Future Communication and Radar)
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