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用于水下无人航行器探测的 MiniSAR 实验系统的关键技术与评估。

Key Technologies and Evaluation of a MiniSAR Experimental System for Unmanned Underwater Vehicle Detection.

机构信息

Institute of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China.

School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China.

出版信息

Sensors (Basel). 2023 Feb 23;23(5):2490. doi: 10.3390/s23052490.

DOI:10.3390/s23052490
PMID:36904699
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10007444/
Abstract

Synthetic aperture radar (SAR) imaging has important application potential in sea environments research, such as submarine detection. It has become one of the most significant research topics in the current SAR imaging field. In order to promote the development and application of SAR imaging technology, a MiniSAR experiment system is designed and developed, which provides a platform for related technology investigation and verification. A flight experiment is then conducted to detect the movement of an unmanned underwater vehicle (UUV) through the wake, which can be captured by SAR. This paper introduces the basic structure and the performance of the experimental system. The key technologies for Doppler frequency estimation and motion compensation, the implementation of the flight experiment, and the image data processing results are given. The imaging performances are evaluated, and the imaging capabilities of the system are verified. The system provides a good experimental verification platform to construct the follow-up SAR imaging dataset of UUV wake and investigate related digital signal processing algorithms.

摘要

合成孔径雷达(SAR)成像在海洋环境研究中具有重要的应用潜力,例如潜艇探测。它已成为当前 SAR 成像领域的最重要研究课题之一。为了促进 SAR 成像技术的发展和应用,设计并开发了一种 MiniSAR 实验系统,为相关技术研究和验证提供了平台。然后进行了飞行实验,通过 SAR 可以捕获无人水下航行器(UUV)在尾流中的运动。本文介绍了实验系统的基本结构和性能。给出了多普勒频率估计和运动补偿的关键技术、飞行实验的实现以及图像数据处理结果。对成像性能进行了评估,验证了系统的成像能力。该系统为构建后续 UUV 尾流 SAR 成像数据集和研究相关数字信号处理算法提供了良好的实验验证平台。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/2f178a8b62a5/sensors-23-02490-g014.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/5cbe0f0ff045/sensors-23-02490-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/2ba665759a4a/sensors-23-02490-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/63fcd9d5f777/sensors-23-02490-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/20155e775a21/sensors-23-02490-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/f9578f247297/sensors-23-02490-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/bba0dbff9b40/sensors-23-02490-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/2f178a8b62a5/sensors-23-02490-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/0123b68dca1f/sensors-23-02490-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/a749a3f98727/sensors-23-02490-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/3994a0e57d4a/sensors-23-02490-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/c887a50d9eea/sensors-23-02490-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/e111dba5bbb1/sensors-23-02490-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/618def6d853b/sensors-23-02490-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/29481779f458/sensors-23-02490-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/5cbe0f0ff045/sensors-23-02490-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/2ba665759a4a/sensors-23-02490-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/63fcd9d5f777/sensors-23-02490-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/20155e775a21/sensors-23-02490-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/f9578f247297/sensors-23-02490-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/bba0dbff9b40/sensors-23-02490-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a47/10007444/2f178a8b62a5/sensors-23-02490-g014.jpg

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The Tacotron-Based Signal Synthesis Method for Active Sonar.基于 Tacotron 的主动声纳信号合成方法。
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