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Near Field Source Localization in the Presence of Array Sensor Position Uncertainties

by Yawar Ali Sheikh, Zhongfu Ye, Rizwan Ullah, Kashif Shabir, Dawei Luo
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Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
Volume 6 - Number 3
Year of Publication: 2016
Authors: Yawar Ali Sheikh, Zhongfu Ye, Rizwan Ullah, Kashif Shabir, Dawei Luo
10.5120/cae2016652437

Yawar Ali Sheikh, Zhongfu Ye, Rizwan Ullah, Kashif Shabir, Dawei Luo . Near Field Source Localization in the Presence of Array Sensor Position Uncertainties. Communications on Applied Electronics. 6, 3 ( Nov 2016), 1-6. DOI=10.5120/cae2016652437

@article{ 10.5120/cae2016652437,
author = { Yawar Ali Sheikh, Zhongfu Ye, Rizwan Ullah, Kashif Shabir, Dawei Luo },
title = { Near Field Source Localization in the Presence of Array Sensor Position Uncertainties },
journal = { Communications on Applied Electronics },
issue_date = { Nov 2016 },
volume = { 6 },
number = { 3 },
month = { Nov },
year = { 2016 },
issn = { 2394-4714 },
pages = { 1-6 },
numpages = {9},
url = { https://www.caeaccess.org/archives/volume6/number3/679-2016652437/ },
doi = { 10.5120/cae2016652437 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-09-04T19:56:43.254684+05:30
%A Yawar Ali Sheikh
%A Zhongfu Ye
%A Rizwan Ullah
%A Kashif Shabir
%A Dawei Luo
%T Near Field Source Localization in the Presence of Array Sensor Position Uncertainties
%J Communications on Applied Electronics
%@ 2394-4714
%V 6
%N 3
%P 1-6
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The accuracy of near-filed source localization is sensitive to the precise knowledge of array sensor positions. Therefore, numerous efforts have been made to propose robust near-field source localization algorithms against array uncertainties. This paper presents the findings attained on the study and investigation of the effects of sensor position uncertainties to the performance of Differential Evolution (DE) algorithm for Direction of Arrival (DOA) and range estimation of near field sources, impinging on a uniform linear array (ULA). Mean square error (MSE) is used as a fitness evaluation function because of its single snapshot requirement to convergence and accurate performance even in negative SNR. The main contribution of this paper is to explore the robustness of DE algorithm against sensor position uncertainties for near-field source localization. The robustness is tested on the basis of a large number of Monte-Carlo simulations and their statistical analysis.

References
  1. Jinzhou L., Hongwei P., Fucheng G., Le Y. and Wenli J. 2015. Localization of multiple disjoint sources with prior knowledge on source locations in the presence of sensor location errors. Digital Signal Processing. 40 (2015), 181-197.
  2. Sheikh Y. A., Ullah R. and Zhonfu Y. 2016. Range and Direction of Arrival Estimation of Near-Field Sources in Sensor Arrays using Differential Evolution Algorithm. International Journal of Computer Applications (IJCA). Vol. 139 (2016), No.4.
  3. Sun M. and Ho K. C. 2012. Refining inaccurate sensor positions using target at unknown location. Signal Processing. 92 (2012), 2097-2104.
  4. Weiss C. and Zoubir A. M. 2014. Robust High-Resolution DOA Estimation with Array Pre-Calibration. In Proceedings of the 22nd European Signal Processing Conference (EUSIPCO).
  5. Ho K. C., Lu X. and Kovavisaruch L. 2007. Source localization using TDOA and FDOA measurements in the presence of receiver location errors: analysis and solution. IEEE Transactions on Signal Processing. 55 (2007), 684–696.
  6. Yang L. and Ho K. C. 2009. An approximately efficient TDOA localization algorithm in closed-form for locating multiple disjoint sources with erroneous sensor positions. IEEE Transactions on Signal Processing. 57 (2009), 4598–4615.
  7. Lui K. W. K., Ma W. K., So H. C. and Chan F. K. W. 2009. Semidefinite programming approach to sensor network node localization with anchor position uncertainty. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’09).
  8. Chiu W., Chen B. and Yang C. 2011. Robust relative location estimation in wireless sensor networks with inexact position problems. IEEE Transactions on Mobile Computing. 99 (2011) 1.
  9. Sun M. and Ho K. C. 2011. An asymptotically efficient estimator for TDOA and FDOA positioning of multiple disjoint sources in the presence of sensor location uncertainties. IEEE Transactions on Signal Processing. 59 (2011), 3434–3440.
  10. Storn R. and Price K. 1997. Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global optimization. 11 (1997), 341-359.
  11. Nishiura T. and Nakamura S. 2003. Talker localization based on the combination of DOA estimation and statistical sound source identification with microphone array. In proceedings of IEEE Workshop on Statistical Signal Processing.
  12. Zaman F., Qureshi I. M., Naveed A. and Khan Z. U. 2012. Joint Estimation of Amplitude, Direction of Arrival and Range of Near Field Sources using Memetic Computing. Progress In Electromagnetics Research C. 31 (2012), 199-213.
  13. Liang J., Liu D., Zeng X., Wang W., Zhang J. and Chen H. 2011. Joint (azimuth-elevation-range) estimation of mixed near-field and far-field sources using two-stage separated steering vector-based algorithm. Progress In Electromagnetics Research. 113 (2011), 17-46.
  14. Raghu N. C. and Sanyogita S. 1995. Higher-order subspace based algorithms for passive localization of near-field sources. In Proceedings of Twenty-Ninth Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA.
  15. Huang Y. D. and Barkat M. 1991. Near-field multiple sources localization by passive sensor array. IEEE Trans. Antennas Propag. 39(7) (1991), 968–975.
  16. Zhou Y. and Feng D. 2006. A new subspace method for the estimation of parameters of near field sources. Journal of Xidian University. 39(5) (2006), 41–45.
  17. Abred-Meraim K. and Hua Y. 1998. 3-D near field source localization using second order statistics. In Proceedings of Conf. Record of the 31st Asilomar Conf. on Signals, Systems and Computers, Pacific Grove, CA, USA.
  18. Zaman F., Qureshi I. M., Naveed A. and Khan Z. U. 2012. Real Time Direction of Arrival estimation in Noisy Environment using Particle Swarm Optimization with single snapshot. Research Journal of Engineering and Technology (Maxwell Scientific organization). 4(13) (2012), 1949-1952.
  19. Zaman F., Khan S. U., Ashraf K. and Qureshi I. M. 2014. An Application of Hybrid Differential Evolution to 3-D Near field Source localization. In Proceedings of 2014 11th International Bhurban Conference on Applied Sciences & Technology (IBCAST) Islamabad, Pakistan.
  20. Ao Y. and Chi H. Experimental Study on Differential Evolution Strategies. In Proceedings of Global Congress on Intelligent Systems, IEEE computer society.
  21. Errasti1 B., Escot D., Poyatos D. and Montiel I. 2009. Performance analysis of the Particle Swarm Optimization algorithm when applied to direction of arrival estimation. In Proceedings of ICEAA.
  22. Addad B., Amari S. and Lesage J. J. 2011. Genetic algorithms for delays evaluation in networked automation systems. Engineering Applications of Artificial Intelligence. 24 (2011), 485-490.
  23. Jiankui Z., Zishu H. and Benyong L. 2006. Maximum Likelihood DOA Estimation Using Particle Swarm Optimization Algorithm. Proc IEEE.
Index Terms

Computer Science
Information Sciences

Keywords

Array uncertainties direction of arrival evolutionary computing near field sensor position error source localization.

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