隧道环境下毫米波雷达多机联合毫米级定位方法

doi:10.11947/j.AGCS.2024.20230352

测绘学报 ›› 2024, Vol. 53 ›› Issue (9): 1679-1693.doi: 10.11947/j.AGCS.2024.20230352

• 精密工程测量 • 上一篇

隧道环境下毫米波雷达多机联合毫米级定位方法

赵胤植¹^,²(), 邹进贵¹^,²(), 张小溪³, 王泽¹, 王鑫哲¹

^1.武汉大学测绘学院，湖北　武汉　430079
^2.武汉大学测绘学院智能监测研究中心，湖北　武汉　430079
^3.中铁第四勘察设计院集团有限公司，湖北　武汉　430063

收稿日期:2023-08-24 发布日期:2024-10-16
通讯作者: 邹进贵 E-mail:yzhzhao@sgg.whu.edu.cn;jgzou@sgg.whu.edu.cn
作者简介:赵胤植（1992—），男，博士后，研究方向为地下空间定位与形变监测、高精度智能监测与装备研制。E-mail：yzhzhao@sgg.whu.edu.cn
基金资助:
湖北省自然科学基金计划青年项目(2024AFB166);国家自然科学基金(41871373);武汉大学地球空间环境与大地测量教育部重点实验室开放基金(21-02-06)

An innovative millimeter-level positioning method for multiple millimeter wave radar network in tunnel environment

Yinzhi ZHAO¹^,²(), Jingui ZOU¹^,²(), Xiaoxi ZHANG³, Ze WANG¹, Xinzhe WANG¹

^1.School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
^2.Research Center for Intelligent Monitoring, School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
^3.China Railway Siyuan Survey and Design Group Co., Ltd., Wuhan 430063, China

Received:2023-08-24 Published:2024-10-16
Contact: Jingui ZOU E-mail:yzhzhao@sgg.whu.edu.cn;jgzou@sgg.whu.edu.cn
About author:ZHAO Yinzhi (1992—), male, post doctor, majors in underground space positioning and deformation monitoring, high-precision intelligent monitoring and equipment development. E-mail: yzhzhao@sgg.whu.edu.cn
Supported by:
The Natural Science Foundation of Hubei Province(2024AFB166);The National Natural Science Foundation of China(41871373);The Key Laboratory of Geospace Environment and Geodesy (Wuhan University), Ministry of Education(21-02-06)

摘要/Abstract

摘要：

随着安全监测智能化时代的到来，隧道环境下监测点定位测量相关研究逐渐向全天候和全天时等方向发展。针对隧道监测点定位时存在实时性较差且测量周期长等问题，同时易受灰尘和照明等因素影响，本文引入具有较高距离与速度分辨率的毫米波雷达开展隧道监测点高精度定位研究，提出一种基于多台毫米波雷达联合测距的定位方法。首先，在快速傅里叶变换提取测距信息的基础上，提出采用线性调频Z变换细化频谱并结合相位差对测距值进行精化，保障测距精度稳定在毫米级；然后，针对传统测距雷达仅能获取一维径向形变的弊端，采用多台毫米波雷达同步观测，建立多机联合定位函数模型，构建了一种顾及单次观测雷达脉冲测量精度差异和先验距离的随机模型；最后，通过隧道试验验证了测距与定位算法精度。结果表明，在无其他干扰的情况下，本文提出的基于线性调频Z变换的相位差法测距精度能达到0.3 mm，算法计算效率较已有方法提高50倍。待测目标稳定的情况下，本文多机联合定位方法X方向精度为2.7 mm,Y方向为0.6 mm，受隧道高度的影响，Z方向精度略低，为6.6 mm。待测目标微动的情况下，该方法能准确探测微小形变，满足监测点全天候、全天时、高精度的实时定位测量需求，并有望在工业结构变形监测中得到应用。

关键词: 隧道环境, 毫米波雷达, 毫米级定位, 结构变形监测, 线性调频Z变换

Abstract:

With the arrival of the intelligent safety monitoring era, research on monitoring point positioning measurement in tunnels and mines is gradually developing towards all-time and all-weather aspects. In response to the problems of poor real-time performance and long measurement period in tunnel monitoring point positioning, as well as susceptibility to factors such as dust and lighting, this paper introduces millimeter wave radar with high distance and speed resolution to conduct high-precision positioning research for tunnel monitoring points. An innovative millimeter-level positioning method for tunnel environment based on multiple millimeter wave radars network is proposed. Firstly, based on the traditional fast Fourier transform to extract ranging information, a method is proposed to refine the frequency spectrum using chirp-Z transform. This method can optimize the ranging observations and ensure ranging accuracy at the millimeter level. Secondly, due to the drawback that traditional ranging radars can only obtain one-dimensional radial deformation, multiple millimeter radars network method is introduced. Further, a functional model for multi machine network positioning is established. In addition, a random model is proposed that takes into account the difference of each millimeter wave radar in radar pulse observation accuracy of each epoch and prior distance. Finally, the precision of ranging and positioning is verified through tunnel tests. The results show that, the phase difference method based on chirp-Z transform proposed in this manuscript can achieve ranging precision within 0.3 mm, and the computational efficiency of the algorithm is improved by 50 times compared to the existing method. When the target to be monitored is stable, the precision of X, Y and Z directions is 2.7 mm, 0.6 mm and 6.6 mm. However, the elevation direction precision is slightly lower due to the influence of tunnel height. In the case of micro movement of the target to be tested, this proposed method can detect small deformations. The method proposed in this manuscript meets the requirements of monitoring point real-time positioning in tunnel environment for all time, high accuracy, and long periods. Furthermore, it is expected to be applied in industrial structure deformation monitoring.

Key words: tunnel environment, millimeter-wave radar, millimeter-level positioning, structure deformation monitoring, chirp-Z transform

中图分类号:

P258

赵胤植, 邹进贵, 张小溪, 王泽, 王鑫哲. 隧道环境下毫米波雷达多机联合毫米级定位方法[J]. 测绘学报, 2024, 53(9): 1679-1693.

Yinzhi ZHAO, Jingui ZOU, Xiaoxi ZHANG, Ze WANG, Xinzhe WANG. An innovative millimeter-level positioning method for multiple millimeter wave radar network in tunnel environment[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(9): 1679-1693.

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组成	特征	属性
FMCW收发器	带宽	60 GHz~64 GHz的覆盖范围具有4 GHz的连续带宽
FMCW收发器	天线	3发4收 TX功率：12 dBm RX噪声系数：12 dB
内部存储器	内存	共1.75 MB 分为MSS程序RAM(512 KB)、 MSS数据RAM(192 KB)、 DSP L1RAM(64 KB)和L2RAM(256 KB) 以及L3雷达数据立方体RAM(768 KB)
其他	电源	I/O支持双电压3.3 V/1.8 V
其他	温度	结温范围为－40~105°C

算法	距离1	距离2	距离3	距离4
补零FFT法64N点	0.121	0.303	0.219	0.300
本文测距方法	0.127	0.296	0.205	0.276

算法	N=256	N=512
补零FFT法64N点	270 336	589 824
本文测距方法	5440	11 840

采样频率/MHz	采样128次/mm	采样256次/mm	采样512次/mm	采样1024次/mm
3.125	206.483	20.362	8.525	2.231
6.25	95.736	13.449	3.094	0.517
12.5	80.317	9.659	2.065	0.247

方向	已有定位方法	本文定位方法
X	5.43	2.73
Y	1.41	0.63
Z	19.60	6.57

隧道环境下毫米波雷达多机联合毫米级定位方法

An innovative millimeter-level positioning method for multiple millimeter wave radar network in tunnel environment

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图/表 19

参考文献 26

相关文章 15

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测量历元阶段	状态	STD/mm			Mean/m
测量历元阶段	状态	X方向	Y方向	Z方向	X方向	Y方向	Z方向
阶段1	静止	2.14	1.71	13.50	9.851 7	5.968 3	4.979 7
阶段2	振动	5.95	6.23	51.18	9.849 4	5.965 3	4.947 9
阶段3	静止	2.11	1.90	15.95	9.847 5	5.961 7	5.006 5
阶段4	振动	12.37	10.47	85.15	9.854 5	5.969 0	4.888 9
阶段5	静止	3.05	3.34	51.44	9.854 7	5.970 5	4.925 5

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方向	角反1	角反2	角反3	角反4
X	2.55	1.52	2.76	2.73
Y	0.91	0.54	1.17	0.63
Z	10.89	10.38	11.63	6.57