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Array and Signal Processing for Radar

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: 31 October 2024 | Viewed by 815

Special Issue Editors


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Guest Editor
College of Electronic Engineering, The National University of Defense Technology, Hefei 230027, China
Interests: radar signal processing; direction of arrival

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Guest Editor
The School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: radar imaging (SAR/ISAR); sparse signal recovery techniques; array signal processing and machine learning techniques

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Guest Editor
Wuhan Electronic Information Institute, Wuhan 410039, China
Interests: multichannel signal detection; statistical and array signal processing
Special Issues, Collections and Topics in MDPI journals
National Lab of Radar Signal Processing, School of Electronic Engineering, Xidian University, Xi’an 710071, China
Interests: waveform diversity; array signal processing; space-time adaptive processing
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Air and Missile Defense College, Air Force Engineering University, Xi’an, China
Interests: radar resource management; target detetcion and tracking; integrated radar and communication system

Special Issue Information

Dear Colleagues,

Inrecent years, considerable progress has been made in developing theories and methodologies for array and signal processing for radar. However, further improved detection, estimation, and imaging performance has been shown to be challenging due to problems associated with the increasingly complex signal environments, such as clutter, jamming, etc. It is important to explore new theories, technologies, and applications in this case.

Specifically, in large-scale multi-input and multi-output systems, the significant increase in array antenna size has brought unprecedented resolution while also creating new requirements for mathematical tools such as signal optimization, feature analysis, and performance evaluation. With the widespread application of artificial intelligence, data-driven machine learning methods have also been introduced into the fields of sensor arrays and signal processing to overcome the performance limitations of traditional model-based methods under non-ideal signal conditions, thus deriving a new pattern of model and data driving. The resource management theory is facing challenges related to ideal environment to electronic antagonism environment, single resource to multiple resource, and convex optimization to non-convex optimization shifts. The above examples all demonstrate the active development trends and enormous application potential in the fields of array and signal processing for radar.

In order to further promote the innovative development of basic theories, key technologies, and applications of array and signal processing for radar, this Special Issue aims to gather the latest research progress in the field of array and signal processing for radar, especially for remote sensing. The types of collected papers will include academic papers and review articles discussing the latest technological achievements. These papers will cover subjects including, but not limited to, the following:

  • Target detection, tracking and imaging;
  • Direction of arrival estimation;
  • Adaptive beamforming ;
  • Radar signal processing based on compressive sensing and sparse optimization theory;
  • Performance bound of parameter estimation;
  • MIMO radar array signal processing;
  • Tensor optimization theory and learning strategies for multidimensional signals;
  • Space-time adaptive signal processing;
  • Machine learning-based radar array and signal processing;
  • Radar array and signal processing for IoT applications.

Prof. Dr. Junpeng Shi
Dr. Yuan Liu
Dr. Weijian Liu
Dr. Jingwei Xu
Dr. Haowei Zhang
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. Remote Sensing 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 2700 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

  • radar array and signal processing
  • waveform and frequency diversity
  • interference, clutter and noise suppression
  • radar imaging
  • radar resource management
  • machine learning
  • space-based radar (SBR) system

Published Papers (1 paper)

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Research

30 pages, 4464 KiB  
Article
Joint Antenna Scheduling and Power Allocation for Multi-Target Tracking under Range Deception Jamming in Distributed MIMO Radar System
by Zhengjie Li, Yang Yang, Ruijun Wang, Cheng Qi and Jieyu Huang
Remote Sens. 2024, 16(14), 2616; https://doi.org/10.3390/rs16142616 - 17 Jul 2024
Viewed by 298
Abstract
The proliferation of electronic countermeasure (ECM) technology has presented military radar with unprecedented challenges as it remains the primary method of battlefield situational awareness. In this paper, a joint antenna scheduling and power allocation (JASPA) scheme is put forward for multi-target tracking (MTT) [...] Read more.
The proliferation of electronic countermeasure (ECM) technology has presented military radar with unprecedented challenges as it remains the primary method of battlefield situational awareness. In this paper, a joint antenna scheduling and power allocation (JASPA) scheme is put forward for multi-target tracking (MTT) in the distributed multiple-input multiple-output (D-MIMO) radar. Aiming at radar resource scheduling in the presence of range deception jamming (RDJ), the false target discriminator is designed based on the Cramer–Rao lower bound (CRLB) in terms of the spoofing range, and the predicted conditional CRLB (PC-CRLB) plays a role in evaluating tracking accuracy. The JASPA scheme integrates the quality of service (QoS) principle to develop an optimization model based on false target discrimination, with the objective of enhancing both the discrimination probability of false targets and the tracking accuracy of real targets concurrently. Since the optimal variables can be separated in constraints, a four-step optimization cycle (FSOC)-based algorithm is developed to solve the multidimensional non-convex problem. Numerical simulation results are provided to illustrate the effectiveness of the proposed JASPA scheme in dealing with MTT in the RDJ environment. Full article
(This article belongs to the Special Issue Array and Signal Processing for Radar)
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