| 引用本文: | 闫紫航， 张 华， 阎 博， 孙景荣. BF体制毫米波雷达设计与点云聚类方法研究[J]. 雷达科学与技术, 2025, 23(5): 513-522.[点击复制] |
| YAN Zihang, ZHANG Hua, YAN Bo, SUN Jingrong. BF System Millimeter-Wave Radar Design and Point Cloud Clustering Method Research[J]. Radar Science and Technology, 2025, 23(5): 513-522.[点击复制] |
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| 摘要: |
| 近些年，毫米波雷达体积小、质量轻、处理速度快以及检测精度高，使其在智慧交通领域的应用越来越广泛。毫米波雷达有着不同的波束体制，原理会有所不同。针对波束合成（Beam Forming, BF）体制毫米波雷达，本文首先介绍了波束合成及扫描原理，进而设计了合适的微带阵列天线，采用四芯片级联的方式，研制雷达硬件射频板；在此基础上，给出雷达探测目标获取数据的流程，结合BF体制雷达下的目标数据及点云特征，提出了一种利用区域生长思想的目标点云聚类方法；最后，通过实测实验，验证了该方法的可行性和有效性，通过对比传统的DBSCAN算法，该方法可以有效解决两个目标距离较近时容易聚成一个目标的问题，同时在点云数较大的情况下可以有效减少处理耗时。该方法为BF体制雷达平台的目标检测、跟踪和识别等应用提供了有力支撑，具有广阔的应用前景和实用价值。 |
| 关键词: 毫米波雷达 四芯片级联 BF体制 区域生长 点云聚类 |
| DOI：DOI:10.3969/j.issn.1672-2337.2025.05.005 |
| 分类号:TN958 |
| 基金项目:国家自然科学基金资助项目（No.61771371）； 陕西省创新能力支持计划（No.2022TD-37） |
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| BF System Millimeter-Wave Radar Design and Point Cloud Clustering Method Research |
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YAN Zihang, ZHANG Hua, YAN Bo, SUN Jingrong
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School of Aerospace Science and Technology, Xidian University, Xi’an 710126, China
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| Abstract: |
| In recent years, millimeter-wave radars have become more and more widely used in the field of smart transportation due to their small size, light weight, fast processing speed and high detection accuracy. Millimeter-wave radars have different beam systems and their principles are different. For beamforming （BF） system millimeter-wave radars, this paper first introduces the principle of beamforming and scanning, and then designs a suitable microstrip array antenna. The radar hardware RF board is developed by cascading four chips. On this basis, the process of obtaining data for radar target detection is given. Combined with the target data and point cloud features under the BF radar, a target point cloud clustering method using the regional growth idea is proposed. Finally, the feasibility and effectiveness of this method are verified through field experiments. By comparing with the traditional DBSCAN algorithm, this method can effectively solve the problem that two targets are easily clustered into one target when the distance between two targets is close. At the same time, it can effectively reduce the processing time when the number of point clouds is large. This method provides strong support for the application of target detection, tracking and recognition of the BF radar platform, and has broad application prospects and practical value. |
| Key words: millimeter-wave radar four-chip cascade BF system regional growth point cloud clustering |
