A Review of Moving Target Detection Techniques Using GNSS Passive Remote Sensing System
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摘要:
全球导航卫星系统（global navigation satellite system,GNSS）除了用于导航定位服务之外,因其信号覆盖率高及卫星可见性强等优势,亦可作为被动雷达的机会辐射源完成地表环境和运动目标的遥感探测。但是,其较低的到达地面功率和较窄的信号带宽也给该类系统的应用带来诸多挑战。回顾了GNSS被动雷达遥感系统近30年的发展历程,聚焦运动目标遥感检测技术。通过分析后向散射和前向散射两种GNSS外辐射源探测体制下的动目标检测流程,梳理了相关技术的重点和难点,介绍了国内外在相关问题上取得的研究进展和潜在发展趋势,以期为相关研究提供参考。
Abstract:The global navigation satellite system (GNSS), besides being utilized for navigation and positioning services, also being regarded as signal source of opportunity for remote sensing of Earth surface environments and spatial targets through its advantages of high signal coverage and satellites visibility. Nevertheless, its inherent characteristics, including low power levels and limited bandwidth, pose considerable challenges to relative applications. The development of GNSS-based passive remote sensing system during the past three decades is reviewed, with a focus on the target detection technology. By analyzing the target detection processes of GNSS-based remote sensing system under both backward and forward scattering configurations, the key points and difficulties of relevant technologies are delineated. Progress and potential opportunities achieved domestically and internationally for addressing relative problems are also discussed.
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http://ch.whu.edu.cn/cn/article/doi/10.13203/j.whugis20240050
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图 1 后向散射探测体制下的GNSS被动雷达遥感系统检测水面动目标的几何结构图
Figure 1. Geometric Configuration of GNSS-Based Backward Scattering Remote Sensing System for Maritime Target Detection
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图 2 前向散射探测体制下的GNSS被动雷达遥感系统探测空中动目标的几何结构图
Figure 2. Geometric Configuration of GNSS-Based Forward Scattering Remote Sensing System for Air Target Detection
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图 3 后向散射探测体制下的GNSS被动雷达遥感系统检测水面动目标结果
Figure 3. Results of Maritime Target Detection with GNSS-Based Passive Backward Scattering Remote Sensing System
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图 4 前向散射体制下的GNSS被动雷达遥感系统检测空中目标结果
Figure 4. Results of Air Target Detection with GNSS-Based Passive Forward Scattering Remote Sensing System
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图 5 前向散射体制下的GNSS被动雷达遥感系统空中目标回波时频分析结果
Figure 5. Time-Frequency Analysis of Air Target Returns of GNSS-Based Passive Forward Scattering Remote Sensing System
表 1 主流RCM补偿方法比较
Table 1 Comparison Amongst Mainstream RCM Correction Methods
算法 补偿阶数 基本原理 特点 KT 1 重映射距离向时间轴 无需速度先验信息,无需搜索；存在多普勒模糊问题 MKT 1 补偿掉与多普勒模糊数相关的相位项,并重映射距离向时间轴 无多普勒模糊问题；复杂度较高,需要反复执行KT SKT 2 使用正负重映射参数分别对信号进行二阶KT并相乘,用以移除相关相位项 可同时校正一阶和二阶RCM,但导致奇数阶DCM参数丢失 RFT 1 使用Radon变换求解目标轨迹的斜率,并对速度和距离进行联合搜索 可在校正RCM的同时获得目标的速度信息,但需要帧内目标速度保持不变 MRFT 1 在RFT基础上增加调频率搜索 可以在校正RCM的同时对一阶DCM进行校正,但要求帧内不存在二阶RCM GRFT N 将目标运动表示为N阶多项式并对相关参数进行遍历搜索 理论上可以在任意时间长度上通过高维搜索实现任意动目标的运动补偿,但实际应用中仍旧需要指定具体阶数 
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表 2 主流多普勒频移时频分析方法比较
Table 2 Comparison Amongst Mainstream Time-Frequency Analysis Methods for Doppler Shift
算法 补偿阶数 基本原理 特点 DFrFT 1 在时频平面按照任意角度进行分数阶傅里叶变换 属于线性时频分析方法,不存在交叉项,但本质上是对调频率的遍历搜索,复杂度较高 DC-DFR分析 1 对DFrFT数值进行重新映射,得到多普勒中心和调频率数据 本质上依旧是DFrFT,但可更直观地考察信号特征和所需估计的参数 LVD分析 1 针对信号的对称参数瞬时自相关函数,引入类似KT的时间轴重映射思想,解耦时间和时延变量 结合了线性和双线性时频分析的优点,理论上具备当前最佳的针对LFM信号的分析性能 STFT N 将时域信号加窗分段,并逐一进行傅里叶变换 线性分析方法,并不局限于特定阶数的时频关系分析,但结果的可用性高度依赖于每段信号的信噪比 WT N 使用一组小波基对信号的频率成分进行逼近和分解 线性时频分析方法,可以很好地分析具有频率突变特征的信号的时频分布,算法的复杂度相对较高
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