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- Title
Intelligent Target Classification Algorithm for 77G Radar Based on Correction Data Set.
- Authors
Zhang, Jing; Jiang, Qing; Fu, Maosheng; Zhou, Xiancun; Jia, Chaochuan; Cai, Cuicui; Zhou, Quan; Liu, Yu; Wu, Xiuhai; Shen, Xiyuan
- Abstract
Traffic participant classification is crucial in autonomous driving perception. Millimeter wave radio detection and ranging radar is a cost-effective and powerful method to perform the task in adverse traffic scenarios, especially in bad inclement weather (e.g. fog, snow and rain) and poor lighting conditions. This paper presents an intelligent target classification algorithm for 77G radar based on correction data set. First, in order to handle the problem that the original data set may easily be interfered by obstacles, the angle information is filtered by analyzing the spatial information of radar signals, which means the interference clutter of obstacles can be effectively removed. Second, the primary data set is corrected using the significant difference between the micro-Doppler of the human body and car. Finally, the characteristic information of the radar signal is extracted, including distance, speed, orientation, micro-Doppler and reflection intensity, and the obtained data sets containing three types of targets (vehicles, human bodies and obstacles) are generated. The generated dynamic and static data sets are collected by sufficient experiments to construct deep learning classification models. The results show that the classification accuracy is improved by the measure of data set correction.
- Subjects
CLASSIFICATION algorithms; RADAR; RADIO waves; INTELLIGENT transportation systems; CLUTTER (Radar); MILLIMETER waves; DEEP learning; BISTATIC radar; ECHO
- Publication
International Journal of Pattern Recognition & Artificial Intelligence, 2023, Vol 37, Issue 16, p1
- ISSN
0218-0014
- Publication type
Article
- DOI
10.1142/S0218001423590231