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引用本文:晋良念,王燃. 毫米波FMCW MIMO雷达三维点云成像方法[J]. 雷达科学与技术, 2022, 20(5): 497-506.[点击复制]
JIN Liangnian, WANG Ran. 3D Point Cloud Imaging Method with FMCW MIMO Millimeter Wave Radar[J]. Radar Science and Technology, 2022, 20(5): 497-506.[点击复制]
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毫米波FMCW MIMO雷达三维点云成像方法
晋良念,王燃
1. 桂林电子科技大学信息与通信学院, 广西桂林 541004;2. 广西无线宽带通信与信号处理重点实验室, 广西桂林 541004
摘要:
毫米波FMCW MIMO雷达的三维点云成像在自动驾驶、智慧交通、工业和安防等领域的三维环境感知因其独特的优势而受到广泛关注。本文在现有处理框架下提出一种结合渐近最小方差稀疏迭代(SAMV)的高分辨点云成像方法。该方法首先对差拍信号做一维快速傅里叶变换(FFT)获得高分辨距离像,然后对每一个距离单元采用SAMV算法来估计方位角网格和俯仰角网格的功率,最后结合CASO-CFAR检测算法,得到探测区域内目标高分辨的距离、方位角和俯仰角三维信息。仿真和实验结果表明,相比现有结合Capon测角的方法,该方法能在相同雷达条件下角分辨率提高2倍,实现了毫米波雷达高分辨的三维成像。
关键词:  毫米波FMCW MIMO雷达  高分辨三维点云像  渐近最小方差方法  迭代方法
DOI:DOI:10.3969/j.issn.1672-2337.2022.05.004
分类号:TN957.52
基金项目:国家自然科学基金(No.61861011, 61461012); 广西自然科学基金(No.2017GXNSFAA198050); 广西无线宽带通信与信号处理重点实验室2020年主任基金项目; 广西创新驱动发展专项(No.桂科AA21077008)
3D Point Cloud Imaging Method with FMCW MIMO Millimeter Wave Radar
JIN Liangnian, WANG Ran
1. School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China;2. Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing, Guilin 541004, China
Abstract:
Three-dimensional (3D) environment perception technology is indispensable in communities such as autonomous driving, smart transportation, industry, and security. The 3D point cloud imaging of millimeter wave FMCW MIMO radar has received extensive research attention due to its unique advantages. This paper combines the asymptotic minimum variance sparse iteration (SAMV) under the existing signal processing framework to propose a high-resolution point cloud imaging method. This method first performs one-dimensional (1D) fast Fourier transform (FFT) on the beat signal to obtain a 1D high-resolution range profile; then uses the SAMV algorithm in each range cell to estimate the power of azimuth and elevation grids. Finally, the CASO-CFAR algorithm is used to detect range, azimuth and elevation 3D information with high-resolution of the target in the detection area. Simulation and experimental results show that, compared with the existing method incorporating Capon angle measurement, this approach can increase the angular resolution by 2 times under the same radar configuration, and realizes high-resolution 3D imaging of millimeter-wave radar.
Key words:  millimeter wave FMCW MIMO radar  high-resolution 3D point cloud image  asymptotic minimum variance method  iterative method

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