UWB雷达在矿山钻孔救援中的应用研究

文虎; 周博; 郑学召; 康玉国; 蔡国斌; 黄渊; 丁文

doi:10.13272/j.issn.1671-251x.18095

UWB雷达在矿山钻孔救援中的应用研究

doi: 10.13272/j.issn.1671-251x.18095

文虎^{1, 2,},
周博¹,
郑学召^{1, 2},
康玉国³,
蔡国斌¹,
黄渊¹,
丁文¹

1.
西安科技大学安全科学与工程学院, 陕西西安　710054
2.
国家矿山救援西安研究中心, 陕西西安　710054
3.
北京大地高科地质勘查有限公司, 北京　100040

基金项目: 国家自然科学基金项目（52174197）；国家重点研发计划项目（2018YFC0808201）；陕西省重点研发计划项目（2023-YBSF-101）。

详细信息

作者简介:
文虎(1972—)，男，新疆石河子人，教授，博士研究生导师，从事煤自燃预测预报、矿井火灾防治理论与技术及井下应急救援等方面的研究工作，E-mail：wenh@xust.edu.cn

中图分类号: TD655
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出版历程
- 收稿日期: 2023-03-30
- 修回日期: 2023-05-26
- 网络出版日期: 2023-06-19

Research on the application of UWB radar in mine drilling rescue

WEN Hu^{1, 2
,},
ZHOU Bo¹,
ZHENG Xuezhao^{1, 2},
KANG Yuguo³,
CAI Guobin¹,
HUANG Yuan¹,
DING Wen¹

1.
College of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, China
2.
Xi'an Research Center of National Mine Rescue, Xi'an 710054, China
3.
Beijing Dadi Hi Tech Geological Exploration Co., Ltd., Beijing 100040, China

摘要

摘要: 超宽带（UWB）雷达探测技术可实现面向钻孔救援的矿井人体目标探测，但UWB电磁波易受灾变矿井复杂环境影响，UWB雷达回波信号易受到灾变矿井背景杂波、环境噪声影响，导致难以实现灾变矿井人体目标精准探测。针对上述问题，介绍了基于UWB雷达的井下目标探测场景及人体目标探测原理，分析了UWB电磁波特性研究现状和UWB回波噪声滤除方法研究现状。总结了存在的问题：① UWB电磁波在灾变矿井复杂环境中的传播特性需深入研究。② 背景杂波产生原因尚未明晰，灾变矿井背景杂波与环境噪声滤除技术研究较少。③ 面向钻孔救援的UWB雷达人体目标探测技术仍需改进。针对现有技术的不足，展望了面向钻孔救援的UWB雷达井下人体目标探测技术的发展趋势：① 深入研究UWB电磁波穿透传输关键表征参数对井下复杂环境特征的敏感程度。② 构建适用于灾变矿井的背景杂波与环境噪声滤除方法。③ 深入优化面向钻孔救援的UWB雷达人体目标探测技术。
- 钻孔救援 /
- UWB雷达 /
- 人体目标探测 /
- UWB电磁波 /
- 传播特性 /
- 噪声滤除
Abstract: The ultra wideband (UWB) radar detection technology can achieve mine human target detection for drilling rescue. However, UWB electromagnetic waves are susceptible to the complex environment of catastrophic mines. The UWB radar echo signals are susceptible to the background clutter and environmental noise of catastrophic mines. It is difficult to achieve precise detection of human targets in catastrophic mines. In order to solve the above problems, the underground target detection scenarios and human target detection principles based on UWB radar are introduced. The research status of UWB electromagnetic wave characteristics and UWB echo noise filtering methods are analyzed. The existing problems are summarized as following points. ① The propagation characteristics of UWB electromagnetic waves in the complex environment of catastrophic mines require in-depth research. ② The reason for the generation of background clutter is not yet clear. There is limited research on the filtering technology of background clutter and environmental noise in catastrophic mines. ③ The UWB radar human target detection technology for drilling rescue still needs to be improved. In response to the shortcomings of existing technologies, the development trend of UWB radar underground human target detection technology for drilling rescue is prospected. ① It is suggested to do in-depth research on the sensitivity of key characterization parameters of UWB electromagnetic wave penetration transmission to complex underground environmental characteristics. ② It is suggested to construct methods for filtering background clutter and environmental noise suitable for catastrophic mines. ③ It is suggested to deeply optimize UWB radar human target detection technology for drilling rescue.
- drilling rescue /
- UWB radar /
- human target detection /
- UWB electromagnetic wave /
- propagation characteristics /
- noise filtering

HTML全文

图 1 基于UWB雷达的井下目标探测场景

Figure 1. Underground target detection scenario based on UWB radar

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图 2 基于UWB雷达的人体目标探测原理

Figure 2. Principle of human target detection based on UWB radar

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图 3 基于UWB雷达的人体目标探测技术研究展望

Figure 3. Prospects for research on human target detection technology based on UWB radar

下载: 全尺寸图片幻灯片

参考文献(32)

[1]	文虎,郭军,金永飞,等. 我国矿井热动力灾害评价研究进展及趋势[J]. 煤矿安全,2016,47(3):172-174,178. WEN Hu,GUO Jun,JIN Yongfei,et al. Progress and trend of evaluation study on coal mine thermodynamic disasters in China[J]. Safety in Coal Mines,2016,47(3):172-174,178.
[2]	李伟. 深部煤炭资源智能化开采技术现状与发展方向[J]. 煤炭科学技术,2021,49(1):139-145. LI Wei. Current status and development direction of intelligent mining technology for deep coal resources[J]. Coal Science and Technology,2021,49(1):139-145.
[3]	齐庆新, 马世志, 孙希奎, 等. 煤矿冲击地压源头防治理论与技术架构[J/OL]. 煤炭学报: 1-14[2023-03-07]. DOI: 10.13225/j.cnki.jccs.2023.0158. QI Qingxin, MA Shizhi, SUN Xikui, et al. Theory and technical framework of coal mine rock burst origin prevention[J/OL]. Journal of China Coal Society: 1-14[2023-03-07]. DOI: 10.13225/j.cnki.jccs.2023.0158.
[4]	郑学召,王虎,文虎,等. 矿井钻孔救援通信技术的研究进展及趋势[J]. 工矿自动化,2017,43(9):41-45. ZHENG Xuezhao,WANG Hu,WEN Hu,et al. Research progress and tendency of mine drilling rescue communication technology[J]. Industry and Mine Automation,2017,43(9):41-45.
[5]	马宏伟,马琨,田海波. 矿山钻孔救援探测机器人研究进展[J]. 工矿自动化,2019,45(2):24-29. MA Hongwei,MA Kun,TIAN Haibo. Research progress of mine drilling rescue detection robots[J]. Industry and Mine Automation,2019,45(2):24-29.
[6]	XU Yanyun,WU Shiyou,CHEN Chao,et al. A novel method for automatic detection of trapped victims by ultrawideband radar[J]. IEEE Transactions on Geoscience and Remote Sensing,2012,50(8):3132-3142. doi: 10.1109/TGRS.2011.2178248
[7]	梁福来,李浩楠,祁富贵,等. UWB MIMO生物雷达多静止人体目标成像方法研究[J]. 雷达学报,2016,5(5):470-476. LIANG Fulai,LI Haonan,QI Fugui,et al. Imaging of multiple stationary humans using a UWB MIMO bio-radar[J]. Journal of Radars,2016,5(5):470-476.
[8]	徐建华,张雨霖,韩勇强. 基于移动节点辅助定位的UWB室内定位方法[J]. 中国惯性技术学报,2023,31(2):141-147. XU Jianhua,ZHANG Yulin,HAN Yongqiang. UWB indoor location method based on moving node auxiliary positioning[J]. Journal of Chinese Inertial Technology,2023,31(2):141-147.
[9]	张铎. 超宽带雷达波在煤中传播规律与定位基础研究[D]. 西安: 西安科技大学, 2018. ZHANG Duo. Fundamental research on propagation law of ultra-wideband radar wave in coal and localiztion [D]. Xi'an: Xi'an University of Science and Technology, 2018.
[10]	肖靖,唐超,常馨月. 微多普勒频移技术用于生命探测中的研究[J]. 数字通信世界,2020(7):8-10. XIAO Jing,TANG Chao,CHANG Xinyue. Study on micro doppler frequency shifting technology for life detection[J]. Digital Communication World,2020(7):8-10.
[11]	胡巍. 基于多普勒雷达的非接触式生命体征检测技术研究[D]. 合肥: 中国科学技术大学, 2014. HU Wei. Non-contact vital sign detection based on doppler radar[D]. Hefei: University of Science and Technology of China, 2014.
[12]	文虎,张铎,郑学召,等. 基于FDTD的电磁波在煤中传播特性[J]. 煤炭学报,2017,42(11):2959-2967. WEN Hu,ZHANG Duo,ZHENG Xuezhao,et al. Propagation characteristics of electromagnetic wave based on FDTD in coal[J]. Journal of China Coal Society,2017,42(11):2959-2967.
[13]	乔欣,孔兵. 井下巷道TOA和TDOA联合估计的UWB定位算法[J]. 煤炭技术,2022,41(5):168-171. QIAO Xin,KONG Bing. UWB positioning algorithm based on joint TOA and TDOA estimation in downhole roadway[J]. Coal Technology,2022,41(5):168-171.
[14]	张国鹏,王艳芬,丁恩杰. 矿井无线多媒体传感器网络UWB信号收发策略研究[J]. 煤炭科学技术,2013,41(12):71-75. ZHANG Guopeng,WANG Yanfen,DING Enjie. Study on UWB signal transmitting and receiving strategy of mine wireless multi-media sensor network[J]. Coal Science and Technology,2013,41(12):71-75.
[15]	何博,李世中,张亚,等. 深埋环境下电磁波传播特性数值分析[J]. 探测与控制学报,2020,42(2):56-60. HE Bo,LI Shizhong,ZHANG Ya,et al. Numerical analysis of deep-buried electromagnetic wave propagation characteristicsin[J]. Journal of Detection & Control,2020,42(2):56-60.
[16]	姚善化,杜斌. 矿井圆形隧道中电磁波传播特性分析[J]. 煤炭科学技术,2015,43(4):88-91. YAO Shanhua,DU Bin. Analysis on propagation features of electromagnetic wave in mine circular type roadway[J]. Coal Science and Technology,2015,43(4):88-91.
[17]	陈瑞鼎,鹿琪,单子涵,等. 基于卡尔曼滤波的超宽带穿墙雷达移动目标探测[J]. 地球物理学进展,2017,32(4):1758-1763. doi: 10.6038/pg20170446 CHEN Ruiding,LU Qi,SHAN Zihan,et al. Moving target detection with the UWB through-wall radar based on Kalman filter[J]. Progress in Geophysics,2017,32(4):1758-1763. doi: 10.6038/pg20170446
[18]	LIANG S D. Sense-through-wall human detection based on UWB radar sensos[J]. Signal Processing,2016,126:117-124. doi: 10.1016/j.sigpro.2015.09.022
[19]	孙公德,郭勇,沈建,等. 分布式超宽带雷达地震被困人员协同探测技术[J]. 震灾防御技术,2017,12(4):966-977. SUN Gongde,GUO Yong,SHEN Jian,et al. Collaborative detection technology for detecting trapped personnel by distributed UWB radar earthquake[J]. Technology for Earthquake Disaster Prevention,2017,12(4):966-977.
[20]	史城,叶盛波,潘俊,等. 一种基于分布式穿墙雷达的复杂条件下人体目标检测方法[J]. 电子与信息学报,2022,44(4):1193-1202. SHI Cheng,YE Shengbo,PAN Jun,et al. A human target detection method under complex conditions by distributed through-wall radar system[J]. Journal of Electronics & Information Technology,2022,44(4):1193-1202.
[21]	白思源,王昭昳,许兆坤,等. 基于多基地IR−UWB生物雷达系统的多人体目标识别定位方法研究[J]. 医疗卫生装备,2021,42(9):1-7,12. BAI Siyuan,WANG Zhaoyi,XU Zhaokun,et al. Research on multiple human targets identification and localization method based on multi-static IR-UWB bio-radar system[J]. Chinese Medical Equipment Journal,2021,42(9):1-7,12.
[22]	高剑飞. 面向穿墙雷达成像的自适应神经网络杂波抑制方法研究[D]. 南昌: 南昌大学, 2022. GAO Jianfei. Research on clutter suppression method of adaptive neural network for through-the-wall radar imaging[D]. Nanchang: Nanchang University, 2022.
[23]	郭继坤,修海林,张显明. 超宽带在煤矿井下穿透障碍物杂波信号的抑制方法[J]. 黑龙江科技大学学报,2015,25(3):328-332. GUO Jikun,XIU Hailin,ZHANG Xianming. Method of inhibition clutter signal on ultra-wideband through obstacles under mine[J]. Journal of Heilongjiang University of Science and Technology,2015,25(3):328-332.
[24]	施端阳,林强,胡冰,等. 基于竞争神经网络的雷达杂波抑制方法[J]. 海军工程大学学报,2022,34(1):67-74. SHI Duanyang,LIN Qiang,HU Bing,et al. Radar clutter suppression method based on competitive neural network[J]. Journal of Naval University of Engineering,2022,34(1):67-74.
[25]	王明泽,李蔚,马俊伟,等. 基于像素向量消除的穿墙雷达杂波抑制算法[J]. 系统工程与电子技术,2022,44(3):827-833. WANG Mingze,LI Wei,MA Junwei,et al. Clutter suppression algorithm based on pixel vector elimination in through-the-wall radar[J]. Systems Engineering and Electronics,2022,44(3):827-833.
[26]	陈焱博. 超宽带穿墙雷达墙体杂波抑制与快速成像方法研究[D]. 南京: 南京信息工程大学, 2021. CHEN Yanbo. The study on clutter suppression and imaging methods of ultra wideband through-the-wall radar[D]. Nanjing: Nanjing University of Information Science and Technology, 2021.
[27]	吴学礼,闫枫,甄然,等. 基于小波变换和K−SVD的探地雷达杂波抑制研究[J]. 河北科技大学学报,2021,42(2):111-118. WU Xueli,YAN Feng,ZHEN Ran,et al. Research on adaptive clutter suppression for ground penetrating radar based on wavelet transform and K-SVD[J]. Journal of Hebei University of Science and Technology,2021,42(2):111-118.
[28]	钱丽,陈婧. 基于小波域KL变换外辐射源雷达杂波抑制算法[J]. 现代雷达,2021,43(3):44-49. QIAN Li,CHEN Jing. Clutter suppression algorithm for external emitter radar based on wavelet domain KL transform[J]. Modern Radar,2021,43(3):44-49.
[29]	ZAMANI A,ABBOSH A. Hybrid clutter rejection technique for improved microwave head imaging[J]. IEEE Transactions on Antennas and Propagation,2015,63(11):4921-4931. doi: 10.1109/TAP.2015.2479238
[30]	王冬霞,张伟,于玲,等. 基于BLSTM神经网络的回声和噪声抑制算法[J]. 信号处理,2020,36(6):991-1000. WANG Dongxia,ZHANG Wei,YU Ling,et al. Echo and noise suppression algorithm based on BLSTM neural network[J]. Journal of Signal Processing,2020,36(6):991-1000.
[31]	田宝凤,周媛媛,王悦,等. 基于独立成分分析的全波核磁共振信号噪声滤除方法研究[J]. 物理学报,2015,64(22):446-457. TIAN Baofeng,ZHOU Yuanyuan,WANG Yue,et al. Noise cancellation method for full-wave magnetic resonance sounding signal based on independent component analysis[J]. Acta Physica Sinica,2015,64(22):446-457.
[32]	李慧,包腾飞,顾冲时. 复杂强噪声下坝体微弱振动响应信号提取[J]. 应用基础与工程科学学报,2020,28(6):1326-1336. doi: 10.16058/j.issn.1005-0930.2020.06.006 LI Hui,BAO Tengfei,GU Chongshi. Signal extraction for weak vibration response of a dam in complex strong noise[J]. Journal of Basic Science and Engineering,2020,28(6):1326-1336. doi: 10.16058/j.issn.1005-0930.2020.06.006