PIER Letters
 
Progress In Electromagnetics Research Letters
ISSN: 1937-6480
Home | Search | Notification | Authors | Submission | PIERS Home | EM Academy
Home > Vol. 58 > pp. 133-139

IMPROVED NLOS ERROR MITIGATION BASED ON LTS ALGORITHM

By J. Khodjaev, S. Tedesco, and B. O'Flynn

Full Article PDF (223 KB)

Abstract:
A new improved Least Trimmed Squares (LTS) based algorithm for Non-line-of sight (NLOS) error mitigation is proposed for indoor localisation systems. The conventional LTS algorithm has hard threshold to decide the final set of base stations (BSs) to be used in position calculations. When the number of Line of Sight (LOS) base stations is more than the number of NLOS BSs the conventional LTS algorithm does not include some of them in position estimation due to principle of LTS algorithm or under heavy NLOS environments it cannot separate least biased BSs to use. To improve the performance of the conventional LTS algorithm in dynamic environments we have proposed a method that selects BSs for position calculation based on ordered residuals without discarding half of the BSs. By choosing a set of BSs which have least residual errors among all combinations as a final set for position calculation, we were able to decrease the localisation error of the system in dynamic environments. We demonstrate the robustness of the new improved method based on computer simulations under realistic channel environments.

Citation:
J. Khodjaev, S. Tedesco, and B. O'Flynn, "Improved NLOS Error Mitigation Based on LTS Algorithm," Progress In Electromagnetics Research Letters, Vol. 58, 133-139, 2016.
doi:10.2528/PIERL15100103

References:
1. http://inlocationalliance.org/, , 2015.
doi:10.1109/TSMCC.2007.905750

2. Hui, L., H. Darabi, P. Banerjee, and L. Jing, "Survey of wireless indoor positioning techniques and systems," IEEE Transactions on Systems, Man, and Cybernetics Part C: Applications and Reviews, Vol. 37, No. 6, 1067-1080, 2007.

3. Farid, Z., R. Nordin, and M. Ismail, "Recent advances in wireless indoor localization techniques and system," Journal of Computer Networks and Communications, Vol. 2013, Article ID 185138, 12 pages, 2013.
doi:10.1016/j.procs.2014.07.078

4. Kul, G., T. Özyer, and B. Tavli, "IEEE 802.11 WLAN based real time indoor positioning: Literature survey and experimental investigations," Procedia Computer Science, Vol. 34, 157-164, 2014.
doi:10.1109/TWC.2012.081612.120045

5. Luo, Y. and C. L. Law, "Indoor positioning using UWB-IR signals in the presence of dense multipath with path overlapping," IEEE Transactions on wireless communications, Vol. 11, No. 10, 3734-3743, 2012.

6. Sahinoglu, Z., S. Gezici, and I. Güvenc, Ultra-wideband Positioning Systems: Theoretical Limits, Ranging Algorithms, and Protocols, Cambridge University Press, 2012.

7. Zhang, V. Y., A.-K. S. Wong, T. W. Kam, and R. W. Ouyang, "Hybrid TOA/AOA-based mobile localization with and without tracking in CDMA cellular networks," IEEE Wireless Communications and Networking Conference (WCNC), 2010, 1-6, 2010.
doi:10.1007/s12243-009-0124-z

8. Khodjaev, J., Y. Park, and A. S. Malik, "Survey of NLOS identification and error mitigation problems in UWB-based positioning algorithms for dense environments," Annals of Telecommunications, Vol. 65, No. 5-6, 301-311, 2010.
doi:10.2528/PIER09020301

9. Tayebi, A., J. Gomez, F. M. Saez de Adana, and O. Gutierrez, "The application of ray-tracing to mobile localization using the direction of arrival and received signal strength in multipath indoor environments," Progress In Electromagnetics Research, Vol. 91, 1-15, 2009.
doi:10.2528/PIER12121208

10. Jiang, J.-J., F.-J. Duan, and J. Chen, "Three-dimensional localization algorithm for mixed near-field and far-field sources based on ESPRIT and MUSIC method," Progress In Electromagnetics Research, Vol. 136, 435-456, 2013.
doi:10.2528/PIER09051703

11. Song, H. B., H.-G. Wang, K. Hong, and L. Wang, "A novel source localization scheme based on Unitary ESPRIT and city electronic maps in urban environments," Progress In Electromagnetics Research, Vol. 94, 243-262, 2009.
doi:10.2528/PIERC13101301

12. 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.

13. Yuan, Y., Z. Yubin, and M. Kyas, "A statistics-based least squares (SLS) method for non-line-of-sight error of indoor localization," IEEE Wireless Communications and Networking Conference (WCNC), 2299-2304, 2013.

14. Li, Z., W. Trappe, Y. Zhang, and B. Nath, "Robust statistical methods for securing wireless localization in sensor networks," Proceedings of IEEE International Symposium on Information Processing in Sensor Networks, 91-98, 2005.
doi:10.1155/ASP/2006/43429

15. Casas, R., A. Marco, J. J. Guerrero, and J. Falco, "Robust estimator for non-line-of-sight error mitigation in indoor localization," Eurasip Journal of Applied Signal Processing, Vol. 2006, No. 1, 1-8, 2006.

16. Gezici, S., I. Guvenc, and Z. Sahinoglu, "On the performance of linear least-squares estimation in wireless positioning systems," IEEE International Conference on Communications, 4203-4208, 2008.
doi:10.1109/LCOMM.2014.2327952

17. Qiao, T. and H. Liu, "Improved least median of squares localization for non-line-of-sight mitigation," IEEE Communications Letters, Vol. 18, No. 8, 1451-1454, 2014.
doi:10.1007/s12243-011-0279-2

18. Khodjaev, J., S. Hur, and Y. Park, "Low complexity LTS-based NLOS error mitigation for localization," Annals of Telecommunications, Vol. 67, No. 9-10, 471-476, 2012.
doi:10.1109/TVT.2008.926071

19. Alsindi, N., B. Alavi, and K. Pahlavan, "Measurement and modeling of ultrawideband TOA-based ranging in indoor multipath environments," IEEE Transactions on Vehicular Technology, Vol. 58, No. 3, 1046-1058, 2009.


© Copyright 2010 EMW Publishing. All Rights Reserved