GBSAR Moving Target Detection Capability Evaluation and Refocus based Detection Algorithm

Proceedings of the 4th International Symposium on Signal Processing Systems Pub Date : 2022-03-25 DOI:10.1145/3532342.3532347

Shuo Wang, Wenjie Shen, Yang Li, Yun Lin, Yanping Wang

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Abstract

Ground Based Synthetic Aperture Radar (GBSAR) can retrieve sub-millimeter deformation information of the mine slope by using differential interferometry, which is important to safe production in mining application. However, the continuous operation of vehicles in the mining area can block radar signal to slope. The movement of vehicles may also affect the slope stability. Therefore, using GBSAR to detect moving target signal and remove their influence to deformation retrieval is necessary. To our knowledge, the paper about moving target detection based on GBSAR has not been published. Considering current GBSAR systems are mostly single channel FMCW systems. In this paper, we evaluate the capability of moving target detection based on NCUT Risk Radar GBSAR. The GBSAR moving target signal model is analyzed. Then, detection methods utilize shift and defocusing characteristics are analyze. According to the analysis, a new time-domain phase compensation method with relative speed for azimuth moving target detection is proposed. The analysis and proposed method are verified by simulated data.

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GBSAR运动目标检测能力评估与重聚焦检测算法

地面合成孔径雷达(GBSAR)利用差分干涉测量技术获取矿山边坡亚毫米级变形信息，对矿山安全生产具有重要意义。然而，在矿区内车辆的连续作业，会遮挡雷达对边坡的信号。车辆的运动也会影响边坡的稳定性。因此，利用GBSAR检测运动目标信号并消除其对变形恢复的影响是必要的。据我们所知，关于基于GBSAR的运动目标检测的论文尚未发表。目前的GBSAR系统多为单通道FMCW系统。本文对基于NCUT风险雷达的运动目标检测能力进行了评估。分析了GBSAR运动目标信号模型。然后分析了利用偏移和散焦特性的检测方法。在此基础上，提出了一种基于相对速度的时域相位补偿方位角运动目标检测方法。仿真数据验证了分析和提出的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 4th International Symposium on Signal Processing Systems

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