Advances in Radar Imaging and Signal Processing

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (20 April 2024) | Viewed by 742

Special Issue Editors


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Guest Editor
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: radar imaging; signal processing

E-Mail Website
Guest Editor
The School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: SAR imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Radar imaging technology is a versatile tool with applications in autonomous navigation, terrain observation, disaster monitoring, moving target tracking, etc. Among the various radar imaging techniques, synthetic aperture radar (SAR) has convincingly demonstrated its unique imaging capabilities, including wide swath coverage, high resolution, and all-day and all-weather operability, which greatly contribute to enhancing the safety, efficiency, and reliability of these applications. Ongoing cutting-edge research in this field is vital to meet the evolving needs of modern society and advanced technologies.

Advanced signal processing techniques enable radar systems to generate high-quality images and extract valuable information from echoes for target detection and recognition. In recent years, new radar imaging technologies have constantly been emerging to meet the increasing application demands, which poses greater challenges to related signal processing techniques. By exploring the symbiotic relationship between these fields, we can gain a deeper understanding of how innovations in signal processing can unlock new possibilities in radar imaging.

This Special Issue aims to introduce the latest advances and future prospects of radar imaging and signal processing, from novel algorithms enhancing resolution and accuracy to applications in environmental monitoring, autonomous vehicles, and disaster management. We encourage discussions and solutions to address the following, but not limited, topics:

  • Spaceborne/airborne SAR/ground-based SAR;
  • UAV/mini-SAR;
  • Bi-static and multi-static SAR/ISAR;
  • InSAR/D-InSAR;
  • Moving target imaging;
  • Video SAR;
  • Microwave photonic radar imaging;
  • New radar imaging technology;
  • Radar surveying and mapping technology;
  • Geohazard monitoring technology;
  • Waveform design and optimization;
  • Target detection and tracking;
  • Data fusion and information fusion;
  • High-speed real-time signal processing;
  • Interference suppression and anti-jamming;
  • Machine learning in radar imaging.

Dr. Zhichao Sun
Dr. Hongyang An
Guest Editors

Manuscript Submission Information

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Keywords

  • radar imaging
  • motion compensation
  • multi-target imaging
  • synthetic aperture radar (SAR)
  • bistatic/multi-static radar imaging
  • forward-looking imaging
  • auto-focusing
  • moving target imaging
  • target detection and tracking
  • radar imaging applications
  • radar data fusion
  • machine learning in radar

Published Papers (1 paper)

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Research

25 pages, 9200 KiB  
Article
Bounding Volume Hierarchy-Assisted Fast SAR Image Simulation Based on Spatial Segmentation
by Ke Wu, Guowang Jin, Xin Xiong and Quanjie Shi
Appl. Sci. 2024, 14(8), 3340; https://doi.org/10.3390/app14083340 - 16 Apr 2024
Viewed by 519
Abstract
In order to improve the simulation efficiency under the premise of ensuring the fidelity of synthetic aperture radar (SAR) simulation images, we propose a BVH-assisted fast SAR image simulation method based on spatial segmentation. The beam scanning model is established based on RD [...] Read more.
In order to improve the simulation efficiency under the premise of ensuring the fidelity of synthetic aperture radar (SAR) simulation images, we propose a BVH-assisted fast SAR image simulation method based on spatial segmentation. The beam scanning model is established based on RD imaging geometric relation, and the bounding volume hierarchy (BVH) algorithm is used to assist in obtaining the time-varying latticed radiation and shadow areas within the radar beam, combining them with the real-time position of the sensors to complete the simulation of the electromagnetic (EM) wave transmission. The ray tracing algorithm is used to calculate the multiple backscatter fields of EM waves, including various material properties of the target surface. The SAR spatial traversal is adopted to spatially segment the latticed radiation area, and the compute unified device architecture (CUDA) kernel function is designed using the echo matrix cell method to make each cell of the target echo matrix as a subfield of the backscattering field, and the position of the echo matrix cell is traversed to obtain the target backscattering field. The target simulated echo is processed by the range Doppler (RD) imaging algorithm to obtain the SAR-simulated image. The simulation results show that compared with a CPU single-thread simulation, the simulation speed of the proposed method is significantly improved, and the SAR simulation image has high structural similarity with the real image, which fully verifies the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Advances in Radar Imaging and Signal Processing)
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