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LIU Jingbin, WANG Zemin, LÜ Xuanfan, LI Wei, YIN Fei, QIU Hongyu. An Indoor Ego-Localization Method for Low Cost Millimeter Wave Radar[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210593
Citation: LIU Jingbin, WANG Zemin, LÜ Xuanfan, LI Wei, YIN Fei, QIU Hongyu. An Indoor Ego-Localization Method for Low Cost Millimeter Wave Radar[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210593

An Indoor Ego-Localization Method for Low Cost Millimeter Wave Radar

doi: 10.13203/j.whugis20210593
Funds:

the National Natural Science Foundation of China,No.41874031,No.42111530064

  • Received Date: 2022-06-21
  • Objectives:Millimeter Wave Radar (mmWave Radar) has been widely used in automotive industry and other fields, but its application is mainly limited to the environmental perception of obstacles or specific tasks. At present, there is little research on the application of mmWave Radar in the field of navigation and positioning. Methods:This paper first studies the raw data processing principle of mmWave Radar, and then designs an indoor ego-localization method which only depends on a low-cost mmWave Radar. The process mainly includes extracting centroid feature points using DBSCAN (density based spatial clustering of applications with noise) algorithm, matching centroid feature point pairs through nearest neighbor criterion, constructing nonlinear optimization function and solving positioning results using LM (Levenberg Marquardt) method. Results:Experiments show that indoor navigation and positioning can be solved in real time by using a low-cost mmWave Radar. Under static conditions, the average horizontal positioning accuracy can reach sub centimeter level (mean value is 0.83cm and standard deviation is 0.47cm). Under dynamic conditions, the absolute trajectory error can reach 0.66m and the average heading angle error can reach 4.58 °, which shows the feasibility of ego-localization of low-cost mmWave Radar. Conclusions:Finally, this paper discusses the problems and feasible research ideas of low-cost mmWave Radar in navigation and positioning.
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    [2] Mur-Artal R, Montiel J M M, Tardós J D.ORB-SLAM:A Versatile and Accurate Monocular SLAM System[J].IEEE Transactions on Robotics, 2015, 31(5):1147-1163
    [3] Qin T, Li P L, Shen S J.VINS-Mono:A Robust and Versatile Monocular Visual-Inertial State Estimator[J].IEEE Transactions on Robotics, 2018, 34(4):1004-1020
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    [7] Cen S H, Newman P.Precise ego-motion estimation with millimeter-wave radar under diverse and challenging conditions[C]//2018 IEEE International Conference on Robotics and Automation.Brisbane, QLD, Australia.:6045-6052
    [8] Cen S H, Newman P.Radar-only ego-motion estimation in difficult settings via graph matching[C]//2019 International Conference on Robotics and Automation (ICRA).Montreal, QC, Canada.:298-304
    [9] Hong Z Y, Petillot Y, Wang S.RadarSLAM:radar based large-scale SLAM in all weathers[C]//2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).Las Vegas, NV, USA.:5164-5170
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An Indoor Ego-Localization Method for Low Cost Millimeter Wave Radar

doi: 10.13203/j.whugis20210593
Funds:

the National Natural Science Foundation of China,No.41874031,No.42111530064

Abstract: Objectives:Millimeter Wave Radar (mmWave Radar) has been widely used in automotive industry and other fields, but its application is mainly limited to the environmental perception of obstacles or specific tasks. At present, there is little research on the application of mmWave Radar in the field of navigation and positioning. Methods:This paper first studies the raw data processing principle of mmWave Radar, and then designs an indoor ego-localization method which only depends on a low-cost mmWave Radar. The process mainly includes extracting centroid feature points using DBSCAN (density based spatial clustering of applications with noise) algorithm, matching centroid feature point pairs through nearest neighbor criterion, constructing nonlinear optimization function and solving positioning results using LM (Levenberg Marquardt) method. Results:Experiments show that indoor navigation and positioning can be solved in real time by using a low-cost mmWave Radar. Under static conditions, the average horizontal positioning accuracy can reach sub centimeter level (mean value is 0.83cm and standard deviation is 0.47cm). Under dynamic conditions, the absolute trajectory error can reach 0.66m and the average heading angle error can reach 4.58 °, which shows the feasibility of ego-localization of low-cost mmWave Radar. Conclusions:Finally, this paper discusses the problems and feasible research ideas of low-cost mmWave Radar in navigation and positioning.

LIU Jingbin, WANG Zemin, LÜ Xuanfan, LI Wei, YIN Fei, QIU Hongyu. An Indoor Ego-Localization Method for Low Cost Millimeter Wave Radar[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210593
Citation: LIU Jingbin, WANG Zemin, LÜ Xuanfan, LI Wei, YIN Fei, QIU Hongyu. An Indoor Ego-Localization Method for Low Cost Millimeter Wave Radar[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210593
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