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交通流检测应用中非扫描多目标毫米波雷达的数据特征分析。

Data Feature Analysis of Non-Scanning Multi Target Millimeter-Wave Radar in Traffic Flow Detection Applications.

机构信息

College of Transportation, Shandong University of Science and Technology, Qingdao 266000, China.

College of Electronics, Communication and Physics, Shandong University of Science and Technology, Qingdao 266000, China.

出版信息

Sensors (Basel). 2018 Aug 21;18(9):2756. doi: 10.3390/s18092756.

DOI:10.3390/s18092756
PMID:30134641
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6163393/
Abstract

The millimeter-wave radar has been widely used in traffic applications. However, little research has been done to install the millimeter-wave radar on the top of a road for detecting road traffic flow at a downward looking direction. In this paper, the vehicle parameters, including the distance, angle and radar cross-section energy, are collected by practical experiments in the aforementioned application scenario. The data features are analyzed from the dimensions of single parameter sampling characteristics and multi-parameter relationships. Further, the correlations of different parameter series are given using the grey correlation analysis method. For millimeter-wave radar used in the traffic flow detection, our work can definitely provide significant support for further intelligent transportation applications, such as vehicle trajectory tracking, traffic flow estimation and traffic event identification.

摘要

毫米波雷达在交通应用中得到了广泛应用。然而,很少有研究将毫米波雷达安装在道路上方,以向下观察方向检测道路交通流量。在本文中,通过实际实验在上述应用场景中收集了车辆参数,包括距离、角度和雷达截面积能量。从单参数采样特征和多参数关系的维度分析了数据特征。进一步,使用灰色关联分析方法给出了不同参数序列之间的相关性。对于用于交通流检测的毫米波雷达,我们的工作肯定可以为进一步的智能交通应用提供重要支持,例如车辆轨迹跟踪、交通流估计和交通事件识别。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/43af1ae7523e/sensors-18-02756-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/506005a4c642/sensors-18-02756-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/74cb5c9e8094/sensors-18-02756-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/68ca2a8e8d24/sensors-18-02756-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/07a2701b8d58/sensors-18-02756-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/4ee87a551dd9/sensors-18-02756-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/0aff944fbffd/sensors-18-02756-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/def52f765de9/sensors-18-02756-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/fab2afdde1ed/sensors-18-02756-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/a981ddb3cdc3/sensors-18-02756-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/43af1ae7523e/sensors-18-02756-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/506005a4c642/sensors-18-02756-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/74cb5c9e8094/sensors-18-02756-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/68ca2a8e8d24/sensors-18-02756-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/07a2701b8d58/sensors-18-02756-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/4ee87a551dd9/sensors-18-02756-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/0aff944fbffd/sensors-18-02756-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/def52f765de9/sensors-18-02756-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/fab2afdde1ed/sensors-18-02756-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/a981ddb3cdc3/sensors-18-02756-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7217/6163393/43af1ae7523e/sensors-18-02756-g010.jpg

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