{"title":"相控阵毫米波雷达射频硬件发展及点云处理方法","authors":"Zihang Yan, Hua Zhang, Bo Yan, Jingrong Sun","doi":"10.1049/sil2/3049323","DOIUrl":null,"url":null,"abstract":"<p>The development of smart transportation has raised the demand for perception and detection of vehicle targets on the road, and compared to traditional methods, such as video cameras, millimeter wave radar applications are becoming increasingly widespread. This article mainly focuses on the research of phased array millimeter wave radar, introduces the principles of beamforming and scanning, designs microstrip array antennas, and develops radar hardware RF boards using a four-chip cascade approach. Further elaborating on the data acquisition process of phased array millimeter wave radar in detecting vehicle targets, based on the obtained point cloud data, combined with the target data and point cloud characteristics under phased array millimeter wave radar, a target point cloud clustering method using the concept of region growing is proposed. Finally, through actual testing and comparison with other clustering algorithms, the superiority of this method in clustering accuracy and processing time was verified. This method can effectively solve the problem of two targets easily converging into one target when they are close, further improving the detection and tracking performance of phased array millimeter wave radar for vehicle targets.</p>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2025 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/sil2/3049323","citationCount":"0","resultStr":"{\"title\":\"Development of RF Hardware and Point Cloud Processing Method for Phased Array Millimeter Wave Radar\",\"authors\":\"Zihang Yan, Hua Zhang, Bo Yan, Jingrong Sun\",\"doi\":\"10.1049/sil2/3049323\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The development of smart transportation has raised the demand for perception and detection of vehicle targets on the road, and compared to traditional methods, such as video cameras, millimeter wave radar applications are becoming increasingly widespread. This article mainly focuses on the research of phased array millimeter wave radar, introduces the principles of beamforming and scanning, designs microstrip array antennas, and develops radar hardware RF boards using a four-chip cascade approach. Further elaborating on the data acquisition process of phased array millimeter wave radar in detecting vehicle targets, based on the obtained point cloud data, combined with the target data and point cloud characteristics under phased array millimeter wave radar, a target point cloud clustering method using the concept of region growing is proposed. Finally, through actual testing and comparison with other clustering algorithms, the superiority of this method in clustering accuracy and processing time was verified. This method can effectively solve the problem of two targets easily converging into one target when they are close, further improving the detection and tracking performance of phased array millimeter wave radar for vehicle targets.</p>\",\"PeriodicalId\":56301,\"journal\":{\"name\":\"IET Signal Processing\",\"volume\":\"2025 1\",\"pages\":\"\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2025-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/sil2/3049323\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/sil2/3049323\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/sil2/3049323","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Development of RF Hardware and Point Cloud Processing Method for Phased Array Millimeter Wave Radar
The development of smart transportation has raised the demand for perception and detection of vehicle targets on the road, and compared to traditional methods, such as video cameras, millimeter wave radar applications are becoming increasingly widespread. This article mainly focuses on the research of phased array millimeter wave radar, introduces the principles of beamforming and scanning, designs microstrip array antennas, and develops radar hardware RF boards using a four-chip cascade approach. Further elaborating on the data acquisition process of phased array millimeter wave radar in detecting vehicle targets, based on the obtained point cloud data, combined with the target data and point cloud characteristics under phased array millimeter wave radar, a target point cloud clustering method using the concept of region growing is proposed. Finally, through actual testing and comparison with other clustering algorithms, the superiority of this method in clustering accuracy and processing time was verified. This method can effectively solve the problem of two targets easily converging into one target when they are close, further improving the detection and tracking performance of phased array millimeter wave radar for vehicle targets.
期刊介绍:
IET Signal Processing publishes research on a diverse range of signal processing and machine learning topics, covering a variety of applications, disciplines, modalities, and techniques in detection, estimation, inference, and classification problems. The research published includes advances in algorithm design for the analysis of single and high-multi-dimensional data, sparsity, linear and non-linear systems, recursive and non-recursive digital filters and multi-rate filter banks, as well a range of topics that span from sensor array processing, deep convolutional neural network based approaches to the application of chaos theory, and far more.
Topics covered by scope include, but are not limited to:
advances in single and multi-dimensional filter design and implementation
linear and nonlinear, fixed and adaptive digital filters and multirate filter banks
statistical signal processing techniques and analysis
classical, parametric and higher order spectral analysis
signal transformation and compression techniques, including time-frequency analysis
system modelling and adaptive identification techniques
machine learning based approaches to signal processing
Bayesian methods for signal processing, including Monte-Carlo Markov-chain and particle filtering techniques
theory and application of blind and semi-blind signal separation techniques
signal processing techniques for analysis, enhancement, coding, synthesis and recognition of speech signals
direction-finding and beamforming techniques for audio and electromagnetic signals
analysis techniques for biomedical signals
baseband signal processing techniques for transmission and reception of communication signals
signal processing techniques for data hiding and audio watermarking
sparse signal processing and compressive sensing
Special Issue Call for Papers:
Intelligent Deep Fuzzy Model for Signal Processing - https://digital-library.theiet.org/files/IET_SPR_CFP_IDFMSP.pdf