Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11): 259-265.doi: 10.11896/jsjkx.220500098

• Computer Network • Previous Articles     Next Articles

WiPasLoc:A Novel Passive Indoor Human Localization Method Based on WiFi

WANG Dong-zi1, GUO Zheng-xin1, GUI Lin-qing1,2, HUANG Hai-ping1,2, XIAO Fu1,2   

  1. 1 School of Computer Science & Technology,Nanjing University of Posts and Telecommunications,Nanjing 210023,China
    2 Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks,Nanjing 210023,China
  • Received:2022-05-12 Revised:2022-07-05 Online:2022-11-15 Published:2022-11-03
  • About author:WANG Dong-zi,born in 1996,postgra-duate.His main research interests include Internet of things and mobile computing.
    XIAO Fu,born in 1980,Ph.D,professor,Ph.D supervisor.His main research interests include areas of Internet of things and mobile computing.
  • Supported by:
    Key Program of National Natural Science Foundation of China (61932013),National Natural Science Foundation of China(61972201)and Natural Science Foundation of Jiangsu Province,China(BK20190068).

PDF (PC)

757

Abstract: Passive indoor human localization is the basis for implementing ubiquitous wireless sensing systems.However,commercial WiFi signals are easily affected by the surrounding environment in our life,which makes it difficult for existing WiFi-based indoor localization works to accurately separate the dynamic human components from the complex received signals.To address this problem,this paper proposes the WiPasLoc,a passive indoor human localization system,which achieves high accuracy indoor localization by using the channel state information(CSI) extracted from commercial WiFi devices.Firstly,the Doppler frequency shift(DFS) estimation is carried out in combination with the signal quality of the CSI subcarriers.Then,the target person signal component is precisely separated from the channel state information by using a double-window-based angle of arrival(AoA) estimation method.Finally,combined with the initial position information of the personnel,accurate passive indoor human localization is achieved by the proposed trajectory fitting algorithm.Experimental results show that the median error of WiPasLoc for indoor personnel trajectory positioning is 80cm,which is 25.9% higher than the existing typical Widar2.0 positioning accuracy.

Key words: WiFi, Indoor Localization, Channel state information(CSI), Doppler frequency shift(DFS)

CLC Number: 

  • TP391
[1]ADIB F M,KABELAC Z,KATABI D,et al.3D tracking via body radio reflections[C]//Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation(NSDI’14).USENIX Association,USA,2014:317-329.
[2]BOCCA M,KALTIOKALLIO O,PATWARI N,et al.Multiple Target Tracking with RF Sensor Networks[J].IEEE Transactions on Mobile Computing,2014,13(8):1787-1800.
[3]ROBERT S,AMANDA L,CHRIS S,et al.Elderly persons’perception and acceptance of using wireless sensor networks to assist healthcare[J].International Journal of Medical Informa-tics,2009,78(12):788-801.
[4]KARANAM C R,KORANY B,MOSTOFI Y.Tracking fromone side:multi-person passive tracking with wifi magnitude measurements[C]//IEEE IPSN.2019:181-192.
[5]TADAYON N,RAHMAN M T,HAN S,et al.Decimeter ranging with channel state information[J].IEEE Transactions on Wireless Communications,2019,18(7):3453-3468.
[6]MANIKANTA K,KIRAN J,DINESH B,et al.SpotFi:Decimeter Level Localization Using WiFi[C]//Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication(SIGCOMM ’15).Association for Computing Machinery,New York,USA,2015:269-282.
[7]SEN S,LEE J K,KIM K H,et al.Avoiding multipath to revive inbuilding WiFi localization[C]//Proceeding of the 11th Annual International Conference on Mobile systems,applications,and services(MobiSys’13).Association for Computing Machinery,New York,NY,USA,2013:249-262.
[8]XIE Y,LI Z,LI M.Precise power delay profiling with commodity WiFi[J].IEEE Transactions on Mobile Computing,2018,18(6):1342-1355.
[9]KOTARU M,JOSHI K,BHARADIA D,et al.Spotfi:Decimeter level localization using wifi[C]//ACM SIGCOMM.2015:269-282.
[10]QIAN K,WU C,ZHOU Z,et al.Inferring motion directionusing commodity WiFi for interactive exergames[C]//ACM CHI.2017:1961-1972.
[11]QIAN K,WU C,ZHANG Y,et al.Widar2.0:Passive human tracking with a single WiFi link[C]//ACM MobiSys.2018:350-361.
[12]ZHOU R,TANG M,GONG Z,et al.Freetrack:Device-free human tracking with deep neural networks and particle filtering[J].IEEE Systems Journal,2019,14(2):2990-3000.
[13]AYYALASOMAYAJULA R,ARUN A,WU C,et al.Deeplearning based wireless localization for indoor navigation[C]//ACM MobiCom.2020:1-14.
[14]CHEN X,LI H,ZHOU C,et al.Fido:Ubiq uitous fine-grained wifi-based localization for unlabelled users via domain adaptation[C]//Proceedings of the Web Conference.2020:23-33.
[15]QIAN K,WU C S,YANG Z,et al.Widar:Decimeter-Level Passive Tracking via Velocity Monitoring with Commodity WiFi[C]//Proceedings of the 18th ACM International Symposium on Mobile Ad Hoc Networking and Computing(Mobihoc’17).Association for Computing Machinery,New York,NY,USA,2017:1-10.
[16]LI X,ZHANG D Q,LV Q,et al.IndoTrack:Device-Free Indoor Human Tracking with Commodity WiFi[J].Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies,2017,1(3):1-22.
[17]WANG Z Q,ZHANG J A,XU M,et al.Single-Target Real-Time Passive WiFi Tracking[J].arXiv:2019.06006,2021.
[18]RAO B D,HARI K S.Performance analysis of root-music[J].IEEE Transactions on Acoustics,Speech,and Signal Processing,1989,37(12):1939-1949.
[19]WU D,ZENG Y W,GAO R Y,et al.WiTraj:Robust indoor motion tracking with WiFi signals[J/OL].IEEE Transactions on Mobile Computing.HTTPS://DOI.ORG/10.1109/TMC.2021.3133114.
[20]NIU K,WANG X,ZHANG F,et al.Rethinking Doppler Effect for Accurate Velocity Estimation with Commodity WiFi Devices[J].IEEE Journal on Selected Areas in Communications,2020,40(7):2164-2178.
[21]GAO R Y,ZHANG M,ZHANG J,et al.Towards position-independent sensing for gesture recognition with Wi-Fi[J].Procee-dings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies,2021:5,(2):1-28.
[1] SHAO Zi-hao, YANG Shi-yu, MA Guo-jie. Foundation of Indoor Information Services:A Survey of Low-cost Localization Techniques [J]. Computer Science, 2022, 49(9): 228-235.
[2] ZHOU Chu-lin, CHEN Jing-dong, HUANG Fan. WiFi-PDR Fusion Indoor Positioning Technology Based on Unscented Particle Filter [J]. Computer Science, 2022, 49(6A): 606-611.
[3] WANG Chi, CHANG Jun. CSI Cross-domain Gesture Recognition Method Based on 3D Convolutional Neural Network [J]. Computer Science, 2021, 48(8): 322-327.
[4] JIA Yu-fu, LI Ming-lei, LIU Wen-ping, HU Sheng-hong, JIANG Hong-bo. Group Perception Analysis Method Based on WiFi Dissimilarity [J]. Computer Science, 2020, 47(10): 63-68.
[5] ZHAI Shu-ying, LI Ru, LI Bo, HAO Shao-yang. Survey on Applications of Visual Crowdsensing [J]. Computer Science, 2019, 46(6A): 11-15.
[6] LIU Jia-hui, WANG Yu-jie, LEI Yi. CSI Gesture Recognition Method Based on LSTM [J]. Computer Science, 2019, 46(11A): 283-288.
[7] DING Ya-san, GUO Bin, XIN Tong, WANG Pei, WANG Zhu, YU Zhi-wen. WiCount:A Crowd Counting Method Based on WiFi Channel State Information [J]. Computer Science, 2019, 46(11): 297-303.
[8] XIA Jun, LIU Jun-fa, JIANG Xin-long, CHEN Yi-qiang. Incremental Indoor Localization for Device Diversity Issues [J]. Computer Science, 2018, 45(10): 69-77.
[9] SHI Zhi-kai and ZHU Guo-sheng. WF-C4.5:Handheld Terminal Traffic Identification Method Based on C4.5 Decision Tree in WiFi Environment [J]. Computer Science, 2017, 44(Z6): 270-273.
[10] HUAN Ruo-hong and CHEN Yue. Indoor Localization Based on Map Information and Particle Filter with Position Adaptive Correction [J]. Computer Science, 2017, 44(Z11): 297-301.
[11] ZHOU A-peng, QIN Xi-zhong, JIA Zhen-hong and NIKOLA Kasabov. Crowdsourcing-based Indoor Localization via Embedded Manifold Matching [J]. Computer Science, 2017, 44(8): 64-70.
[12] SHA Chao-heng, XIAO Fu, CHEN Lei, SUN Li-juan and WANG Ru-chuan. Fingerprint-based Indoor Localization via Matrix Completion [J]. Computer Science, 2016, 43(6): 91-96.
[13] XI Rui, LI Yu-jun and HOU Meng-shu. Survey on Indoor Localization [J]. Computer Science, 2016, 43(4): 1-6.
[14] ZHONG Wei-bo,LI Zhong-mei,SHI Jie and CHEN Zhong-ming. Design and Implementation of ZigBee-WiFi Gateway for Facility Agriculture [J]. Computer Science, 2014, 41(Z6): 484-486.
[15] ZHU Er-xi and XU Min. New Research and Design of Intelligent Information Collector of Traffic Violation [J]. Computer Science, 2014, 41(Z11): 478-481.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.