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Array Digital Signal Processing for Radar

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

Deadline for manuscript submissions: closed (15 April 2025) | Viewed by 180

Special Issue Editor


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Guest Editor
National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
Interests: radar signal processing; array signal processing; synthetic aperture radar
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Array digital signal processing (DSP) plays a pivotal role in radar technology. By optimizing signal reception, improving resolution, and mitigating interference, it enhances radar performance, thereby increasing the application value of radar technology in various fields, such as weather detection and autonomous driving. This Special Issue focuses on the latest advancements in array digital signal processing technology for radar applications. Topics of interest include adaptive beamforming, direction of arrival (DOA) estimation, clutter suppression, and weak target detection in complex environments. Additionally, contributions on array DSP-based synthetic aperture radar (SAR) imaging, including array SAR signal processing, 2D/3D SAR imaging, SAR interferometry, and polarimetry, are also welcome, as these have become indispensable components of high-resolution radar imaging and remote sensing applications. Original research and reviews addressing current challenges and proposing innovative DSP solutions for both conventional and emerging radar technologies are invited.

Prof. Dr. Linrang Zhang
Guest Editor

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Keywords

  • array digital signal processing (DSP) for radar
  • weak target detection
  • adaptive beamforming
  • array synthetic aperture radar (SAR) 2D/3D imaging

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Published Papers (1 paper)

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Research

23 pages, 2319 KiB  
Article
Codesign of Transmit Waveform and Receive Filter with Similarity Constraints for FDA-MIMO Radar
by Qiping Zhang, Jinfeng Hu, Xin Tai, Yongfeng Zuo, Huiyong Li, Kai Zhong and Chaohai Li
Remote Sens. 2025, 17(10), 1800; https://doi.org/10.3390/rs17101800 - 21 May 2025
Abstract
The codesign of the receive filter and transmit waveform under similarity constraints is one of the key technologies in frequency diverse array multiple-input multiple-output (FDA-MIMO) radar systems. This paper discusses the design of constant modulus waveforms and filters aimed at maximizing the signal-to-interference-and-noise [...] Read more.
The codesign of the receive filter and transmit waveform under similarity constraints is one of the key technologies in frequency diverse array multiple-input multiple-output (FDA-MIMO) radar systems. This paper discusses the design of constant modulus waveforms and filters aimed at maximizing the signal-to-interference-and-noise ratio (SINR). The problem’s non-convexity renders it challenging to solve. Existing studies have typically employed relaxation-based methods, which inevitably introduce relaxation errors that degrade system performance. To address these issues, we propose an optimization framework based on the joint complex circle manifold–complex sphere manifold space (JCCM-CSMS). Firstly, the similarity constraint is converted into the penalty term in the objective function using an adaptive penalty strategy. Then, JCCM-CSMS is constructed to satisfy the waveform constant modulus constraint and filter norm constraint. The problem is projected into it and transformed into an unconstrained optimization problem. Finally, the Riemannian limited-memory Broyden–Fletcher–Goldfarb–Shanno (RL-BFGS) algorithm is employed to optimize the variables in parallel. Simulation results demonstrate that our method achieves a 0.6 dB improvement in SINR compared to existing methods while maintaining competitive computational efficiency. Additionally, waveform similarity was also analyzed. Full article
(This article belongs to the Special Issue Array Digital Signal Processing for Radar)
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