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摘要: 超宽带穿墙雷达具备穿透墙体的能力，结合多输入多输出(MIMO)技术可以实现墙体后侧隐蔽目标的成像，为建筑物内人员检测和定位提供了丰富的信息。该文基于调频连续波(FMCW)体制下的多发多收超宽带穿墙雷达系统，提出了一种闭环干涉校准方法，校正了由系统内部误差产生的图像散焦。墙体的存在会导致目标成像位置偏离真实位置，该文推导了联合通道和像素点的三维墙体补偿算法，并基于其几何特性，提出快速重聚焦算法。首先去除墙体影响、确定目标存在区域；鉴于区域几何特性，选择适应区域形状的球坐标网格划分；分区域进行局部重聚焦，避免了因电磁波衰减导致成像结果中出现强目标掩盖弱目标的现象，并且球坐标形式的网格划分和局部成像大大缩减了算法耗时。通过仿真分析与实验验证，该文提出的系统校准方法能有效补偿系统误差，快速重聚焦算法可以实现墙后人体多目标三维定位，各维度定位精度优于10 cm，计算效率相对其余算法提升了5倍左右。从目标检测概率方面，所提算法相比其余算法不会出现弱目标的漏检。Abstract: Ultra-wideband through-wall radar, leveraging its ability to penetrate walls, can be used together with Multiple-Input Multiple-Output (MIMO) technology to image hidden targets behind walls. This approach provides rich information for detecting and locating people within buildings. This paper introduces a closed-loop interferometric calibration method based on a multitransmitter multireceiver ultrawideband wall-penetrating radar system in the Frequency Modulated Continuous Wave (FMCW) regime. This method aims to correct scattering issues caused by internal system errors. The presence of walls causes the target imaging position to deviate from the real position. To address this, this paper derives a three-Dimensional (3D) wall compensation algorithm jointing channels and pixel points. Then, a fast refocusing algorithm is proposed based on the geometric properties of the imaging area. The first step involves removing the influence of walls on delay time and determining the presence of the target. Subsequently, in view of the geometric properties of the region, a spherical coordinate grid division adapted to the region shape is selected. Localized refocusing is then performed in the subregion. This avoids the issue of electromagnetic wave attenuation, causing strong targets to mask weak ones in the imaging results. At the same time, the adoption of spherical coordinates for gridding and localized imaging greatly reduces the overall time consumption by the algorithm. Through simulation analysis and experimental verification, the proposed calibration method can effectively compensate for system errors. The fast refocusing algorithm can be used to realize multitarget 3D localization of the human body behind walls, with the localization accuracy of each dimension surpassing 10 cm and computational speeds improving by five times compared with those of existing algorithms. In terms of target detection probability, the proposed algorithm consistently identifies weak targets that other algorithms may overlook.
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图 4 校准前后角反射器三维成像结果
Figure 4. 3D imaging results of the corner reflector before and after calibration
图 17 所提算法两个人体目标成像结果
Figure 17. The imaging results of two human targets using the proposed algorithm
图 18 两个人体目标各方法三维成像结果
Figure 18. The 3D imaging results of two human targets using various algorithms
图 20 3个人体目标中心通道回波距离-慢时间分布
Figure 20. Center channel echo range-slow time distribution of three human targets
图 21 所提算法3个人体目标成像结果
Figure 21. The imaging results of three human targets using the proposed algorithm
图 22 3个人体目标各方法三维成像结果
Figure 22. The 3D imaging results of three human targets using various algorithms
表 1 仿真参数表
Table 1. Simulation parameter table
参数 指标 墙体厚度${D_{\mathrm{w}}}$ 37 cm 相对介电常数${\varepsilon _{\mathrm{r}}}$ 6 天线阵列 4发7收 信号波形 Ricker子波 目标位置 (1.5, 1.0, 1.0) 
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表 2 各方法定位精度对比(m)
Table 2. Comparison of positioning accuracy among various methods (m)
所用算法 x y z $|\Delta x|$ ($|\Delta x|/x$) $|\Delta y|$ ($\Delta y|/y$) $|\Delta z|$ ($|\Delta z|/z$) $\delta p$ 理想 1.5 1.0 1.0 — — — 传统算法 2.145 1.44 0.9877 0.645 (43%) 0.44 (44%) 0.0123 (1.23%)0.645 文献[16] 1.935 1.3 0.896 0.435 (22.48%) 0.3 (30%) 0.104 (10.4%) 0.435 文献[19] 1.4375 0.966 1.1634 0.0625 (4.17%)0.034 (3.4%) 0.1634 (16.34%)0.1634 所提算法 1.5408 1.0121 0.996 0.0408 (2.72%)0.0121 (1.21%)0.004 (0.4%) 0.0408
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表 3 实验一各方法对目标1定位精度对比(m)
Table 3. Comparison of positioning accuracy of target 1 using various methods in the first experiment (m)
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表 4 目标位置(m)
Table 4. Target position (m)
序号 坐标 目标1 (0, 0.6, 2.7) 目标2 (1.6, 0.1, 4.5) 目标3 (–4.4, 0.1, 5.3)
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表 5 实验二各方法对目标1定位精度对比(m)
Table 5. Comparison of positioning accuracy of target 1 using various methods in the second experiment (m)
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表 6 实验二各方法对目标2定位精度对比(m)
Table 6. Comparison of positioning accuracy of target 2 using various methods in the second experiment (m)
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表 7 实验三各方法对目标1定位精度对比(m)
Table 7. Comparison of positioning accuracy of target 1 using various methods in the third experiment (m)
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