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Device-free multi-target localization method using phase-shift-based compressive sensing

  • SHENG Jinfeng ,
  • LI Ning ,
  • GUO Yan ,
  • CHEN Cheng ,
  • LI Huajing
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  • College of Communications Engineering, Army Engineering University of PLA, Nanjing 210007, China

Received date: 2022-01-06

  Revised date: 2022-06-21

  Online published: 2022-05-23

Abstract

Device-free localization(DFL),as a new localization technology,is a hotspot in passive sensing such as security monitoring,intrusion detection and contact tracking.It locates the target by analyzing the shadow effect of passive target on wireless link.Phase is an important characteristic of wireless signal,which is more fine-grained than signal strength.To improve the localization performance,we use phase information of wireless links and propose a device-free multi-target localization method using phase shift based compressive sensing.In this method, the phase shift of received signal is taken as the observation data, and the sparse vector of target position is recovered by variational Bayesian inference.Simulation results show that in the monitoring area of 6.5 m×6.5 m,the average localization error of RSS method is 0.579 0 m, while the average localization error of this method is 0.254 7 m,the localization accuracy is improved by more than one times,and it can achieve robust DFL.

Cite this article

SHENG Jinfeng , LI Ning , GUO Yan , CHEN Cheng , LI Huajing . Device-free multi-target localization method using phase-shift-based compressive sensing[J]. Journal of University of Chinese Academy of Sciences, 2024 , 41(2) : 241 -248 . DOI: 10.7523/j.ucas.2022.066

References

[1] Boukerche A, Oliveira H A B F, Nakamura E F, et al. Localization systems for wireless sensor networks[J]. IEEE Wireless Communications, 2007, 14(6): 6-12. DOI: 10.1109/MWC.2007.4407221.
[2] Deak G, Curran K, Condell J. A survey of active and passive indoor localisation systems[J]. Computer Communications, 2012, 35(16): 1939-1954. DOI: 10.1016/j.comcom.2012.06.004.
[3] Khalajmehrabadi A, Gatsis N, Akopian D. Modern WLAN fingerprinting indoor positioning methods and deployment challenges[J]. IEEE Communications Surveys & Tutorials, 2017, 19(3): 1974-2002. DOI: 10.1109/COMST.2017.2671454.
[4] Kirsch F, Gottinger M, Dobrev Y, et al. Advanced wireless local positioning via compressed sensing[J]. IEEE Access, 2018, 6: 25110-25120. DOI: 10.1109/ACCESS.2018.2829619.
[5] Lei Q, Zhang H J, Sun H, et al. A new elliptical model for device-free localization[J]. Sensors (Basel, Switzerland), 2016, 16(4): 577. DOI: 10.3390/s16040577.
[6] Wang J, Gao Q H, Pan M, et al. Device-free wireless sensing: challenges, opportunities, and applications[J]. IEEE Network, 2018, 32(2): 132-137. DOI: 10.1109/MNET.2017.1700133.
[7] Zhou Z M, Wu C S, Yang Z, et al. Sensorless sensing with WiFi[J]. Tsinghua Science and Technology, 2015, 20(1): 1-6. DOI: 10.1109/TST.2015.7040509.
[8] Talampas M C R, Low K S. A geometric filter algorithm for robust device-free localization in wireless networks[J]. IEEE Transactions on Industrial Informatics, 2016, 12(5): 1670-1678. DOI: 10.1109/TII.2015.2433211.
[9] 史达亨, 刘立刚, 周斌, 等. 跨时间迁移的多源无线信号指纹融合定位方法[J]. 中国科学院大学学报, 2021, 38(6): 817-824. DOI: 10.7523/j.issn.2095-6134. 2021.06.012.
[10] Wang Q H, Yiğitler H, Jäntti R, et al. Localizing multiple objects using radio tomographic imaging technology[J]. IEEE Transactions on Vehicular Technology, 2016, 65(5): 3641-3656. DOI: 10.1109/TVT.2015.2432038.
[11] 孙保明, 郭艳, 李宁, 等. 无线传感器网络中基于压缩感知的动态目标定位算法[J]. 电子与信息学报, 2016, 38(8): 1858-1864. DOI: 10.11999/JEIT151203.
[12] Yang S X, Guo Y, Li N, et al. Compressive sensing based device-free multi-target localization using quantized measurement[J]. IEEE Access, 2019, 7: 73172-73181. DOI: 10.1109/ACCESS.2019.2920482.
[13] Zhang D, Ma J, Chen Q B, et al. An RF-based system for tracking transceiver-free objects[C]// Fifth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom). March 19-23, 2007, White Plains, NY, USA. IEEE, 2007: 135-144. DOI: 10.1109/PERCOM.2007.8.
[14] Wilson J, Patwari N. A fade-level skew-Laplace signal strength model for device-free localization with wireless networks[J]. IEEE Transactions on Mobile Computing, 2012, 11(6): 947-958. DOI: 10.1109/TMC.2011.102.
[15] Rampa V, Savazzi S, D’Amico M, et al. Dual-target body model for device-free localization applications[C]//2019 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC). September 9-13, 2019, Granada, Spain. IEEE, 2019: 181-186. DOI: 10.1109/APWC.2019.8870574.
[16] Wang J, Gao Q H, Pan M, et al. Toward accurate device-free wireless localization with a saddle surface model[J]. IEEE Transactions on Vehicular Technology, 2016, 65(8): 6665-6677. DOI: 10.1109/TVT.2015.2476495.
[17] Yu D P, Guo Y, Li N, et al. SA-M-SBL: an algorithm for CSI-based device-free localization with faulty prior information[J]. IEEE Access, 2019, 7: 61831-61839. DOI: 10.1109/ACCESS.2019.2916194.
[18] Ma Y T, Wang B B, Ning W R, et al. PRSRTI: a novel device-free localization method using phase response shift based radio tomography imaging[J]. IEEE Transactions on Vehicular Technology, 2020, 69(11): 13812-13820. DOI: 10.1109/TVT.2020.3027957.
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