| 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(BF, Beam Forming)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了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： |
| 分类号:TN958 |
| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目） |
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| BF System Millimeter Wave Radar Design and Point Cloud Clustering Method Research |
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| Abstract: |
| In recent years, millimeter-wave radars are increasingly 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) millimeter-wave radars, this paper first introduces the principles 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 radar detecting targets to obtain data 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 the traditional DBSCAN algorithm, this method can effectively solve the problem that two targets are easily clustered into one target when the distance is close, and 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 target detection, tracking and recognition applications of the BF radar platform, and has broad application prospects and practical value. |
| Key words: millimeter-wave radars four chip cascade beam forming regional growth point cloud clustering |