隧道环境毫米波雷达目标识别与分类算法

doi:10.12305/j.issn.1001-506X.2025.05.08

Abstract

Abstract:

Millimeter wave (MMW) radar exhibits all-weather capability, high precision, low cost, and non-contact sensing, rendering it highly suitable for safety monitoring in tunnels. However, due to severe multipath interference in tunnels, classical signal processing algorithms have a high error rate in target recognition. The high computational complexity and poor real-time performance of three-dimensional (3D) convolutional deep learning algorithms hinder the application of MMW radar in tunnels. To regard this, an efficient deep-learning algorithm scheme is proposed, which can achieve high-precision real-time positioning and classification of targets such as individuals, vehicles, and other targets. The algorithm utilizes a signal processing method to compress and encode the radar intermediate frequency data across multiple dimensions, uses Mamba network to extract features from radar spatio-temporal sequence data, uses heatmap of field data to estimate target location, and uses only local regional features of target location to estimate target category, avoiding incoherent regional signal interference and improving target recognition accuracy. The algorithm is designed based on two-dimensional (2D) convolution, and a nonlinear mapping relationship between radar data and target location and category is established, effectively managing computational complexity. Experiments in the tunnel show that the mean intersection over union (mIoU), average precision (AP) and speed of the algorithm are respectively 0.68, 65.26%, 22.5 ms/frame, compared with the 3D convolutional CenterRadarNet algorithm, mIoU is reduced by 3%, AP is increased by 9%, and speed is increased by 53.3%, which proves that the algorithm has good performance and has application value in actual application.

Key words: millimeter wave (MMW) radar, target recognition, real time, deep learning, tunnel

CLC Number:

TN958.94

Zhijie JIANG, Heng SONG, Nan HU, Lanxi DUAN, Ping CAO. Target recognition and classification algorithm of MMW radar in tunnel[J]. Systems Engineering and Electronics, 2025, 47(5): 1453-1460.

Figures/Tables 9

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参数名	参数值
起始频率/GHz	60
调频斜率/(MHz/μs)	79
扫频带宽/GHz	3.16
采样率/MSPS	12.5
采样点数	64
每帧chirp数	32
帧周期/ms	20
通道数	3个发射天线, 4个接收天线

评价指标	本文方法		CenterRadarNet
评价指标	车库	隧道	车库	隧道
mIoU	0.69	0.68	0.72	0.70
AP/%	67.04	65.26	61.15	59.84
速度/(ms/frame)	20.6	22.5	46.9	48.2

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Target recognition and classification algorithm of MMW radar in tunnel

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