Vol. 47

Front:[PDF file] Back:[PDF file]
Latest Volume
All Volumes
All Issues
2016-04-02

Device-Free Electromagnetic Passive Localization with Frequency Diversity

By Wei Ke, Yanan Yuan, Xiunan Zhang, and Jianhua Shao
Progress In Electromagnetics Research M, Vol. 47, 129-139, 2016
doi:10.2528/PIERM15102502

Abstract

As an emerging wireless localization technique, the electromagnetic passive localization without the need of carrying any device, named device-free passive localization (DFPL) technique has drawn considerable research attentions. The DFPL technique detects the shadowed links in the monitored area and realizes localization with the received signal strength (RSS) measurements of these links. However, the current RSS-based DFPL techniques have two major challenges: one is that the RSS signal is particularly sensitive to noise and another one is that it needs the large number of nodes to provide enough RSS measurements of wireless links to guarantee good performance. To overcome these problems, in this paper we take advantage of compressive sensing (CS) theory to handle the spatial sparsity of the DFPL problem for reducing the number of nodes required by DFPL systems and exploit the frequency diversity technique to deal with the problem of the RSS sensitivity. Meanwhile, inspired by the fact that the target's movement is continuous and the target's current location must be around the last location, we add prior information on the support region into the sparse reconstruction process for enhancing sparse reconstruction performance. The effectiveness and robustness of the proposed scheme are demonstrated by experimental results where the proposed algorithm yields substantial improvement for localization performance.

Citation


Wei Ke, Yanan Yuan, Xiunan Zhang, and Jianhua Shao, "Device-Free Electromagnetic Passive Localization with Frequency Diversity," Progress In Electromagnetics Research M, Vol. 47, 129-139, 2016.
doi:10.2528/PIERM15102502
http://www.jpier.org/PIERM/pier.php?paper=15102502

References


    1. Mitilineos, S. A. and S. C. A. Thomopoulos, "Positioning accuracy enhancement using error modeling via a polynomial approximation approach," Progress In Electromagnetics Research, Vol. 102, 49-64, 2010.
    doi:10.2528/PIER10010102

    2. Mitilineos, S. A., D. M. Kyriazanos, O. E. Segou, J. N. Goufas, and S. C. A. Thomopoulos, "Indoor localization with wireless sensor networks," Progress In Electromagnetics Research, Vol. 109, 441-474, 2010.
    doi:10.2528/PIER10062801

    3. Patwari, N. and J. Wilson, "RF sensor networks for device-free localization: Measurements, models, and algorithms," Proc. of the IEEE, Vol. 98, No. 11, 1961-1973, 2010.
    doi:10.1109/JPROC.2010.2052010

    4. Youssef, M., M. Mah, and A. Agrawala, "Challenges: Device-free passive localization for wireless environments," 13th ACM MobiCom., 222-229, 2007.

    5. Sabek, I., M. Youssef, and A. V. Vasilakos, "ACE: An accurate and efficient multi-entity device-free WLAN localization system," IEEE Transactions on Mobile Computing, Vol. 14, No. 2, 261-273, 2015.
    doi:10.1109/TMC.2014.2320265

    6. Zhang, D., J. Ma, Q. Chen, and L. M. Ni, "An RF-based system for tracking transceiver-free objects," Proc. 5th PerCom., 135-144, 2007.

    7. Zhang, D., K. Lu, R. Mao, Y. Feng, Y. Liu, Z. Ming, and L. Ni, "Fine-grained localization for multiple transceiver-free objects by using RF-based technologies," IEEE Trans. Parallel Distrib. Syst., Vol. 25, No. 6, 1464-1475, 2014.
    doi:10.1109/TPDS.2013.243

    8. Wilson, J. and N. Patwari, "Radio tomographic imaging with wireless networks," IEEE Transactions on Mobile Computing, Vol. 9, No. 5, 621-632, 2010.
    doi:10.1109/TMC.2009.174

    9. Kaltiokallio, O., M. Bocca, and N. Patwari, "A fade level-based spatial model for radio tomographic imaging," IEEE Transactions on Mobile Computing, Vol. 13, No. 5, 1159-1172, 2014.

    10. Kanso, M. A. and M. G. Rabbat, "Compressed RF tomography for wireless sensor networks: Centralized and decentralized approaches," Proc. 5th DCOSS, 173-186, 2009.

    11. Yang, Z. Y., K. D. Huang, X. M. Guo, and G. L. Wang, "A real-time device-free localization system using correlated RSS measurements," EURASIP J. Wireless Commu. Netw., Vol. 2013, No. 186, 1-12, 2013.

    12. Wang, J., Q. Gao, X. Zhang, and H. Wang, "Device-free localization with wireless networks based on compressing sensing," IET Commun., Vol. 6, No. 15, 2395-2403, 2012.
    doi:10.1049/iet-com.2011.0603

    13. Ke, W., G. Liu, and T. Fu, "Robust sparsity-based device-free passive localization in wireless networks," Progress In Electromagnetics Research C, Vol. 46, 63-73, 2014.
    doi:10.2528/PIERC13101301

    14. Kaltiokallio, O., M. Bocca, and N. Patwari, "Enhancing the accuracy of radio tomographic imaging using channel diversity," Proc. 9th IEEE Int. Conf. MASS, 254-262, 2012.

    15. Hamilton, B. R., X. L. Ma, R. J. Baxley, and S. M. Matechik, "Propagation modeling for radio frequency tomography in wireless networks," IEEE J. Sel. Topics Signal Process, Vol. 8, No. 1, 43-54, 2014.
    doi:10.1109/JSTSP.2013.2287471

    16. Zhao, Y. and N. Patwari, "Demo abstract: Histogram distance-based radio tomographic localization," Proc. 11th ACM/IEEE Int. Conf. IPSN, 129-130, 2012.

    17. Candès, E. J. and M. B. Waki, "An introduction to compressive sampling," IEEE Signal Process. Mag., Vol. 25, No. 2, 21-30, 2008.
    doi:10.1109/MSP.2007.914731

    18. Miosso, C. J., R. Von Borries, and J. H. Pierluissi, "Compressive sensing with prior information: Requirements and probabilities for reconstruction in l1-minimization," IEEE Trans Signal Process., Vol. 61, No. 9, 2150-2164, 2013.
    doi:10.1109/TSP.2012.2231076

    19. Scarlett, J., J. S. Evans, and S. Dey, "Compressed sensing with prior information: information-theoretic limits and practical decoders," IEEE Trans. Signal Process., Vol. 61, No. 2, 427-439, 2013.
    doi:10.1109/TSP.2012.2225051