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

Yawar Ali Sheikh, Zhongfu Ye, Rizwan Ullah, Kashif Shabir, Dawei Luo. Published in Signal Processing.

Communications on Applied Electronics
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Yawar Ali Sheikh, Zhongfu Ye, Rizwan Ullah, Kashif Shabir, Dawei Luo

Yawar Ali Sheikh, Zhongfu Ye, Rizwan Ullah, Kashif Shabir and Dawei Luo. Near Field Source Localization in the Presence of Array Sensor Position Uncertainties. Communications on Applied Electronics 6(3):1-6, November 2016. BibTeX

	author = {Yawar Ali Sheikh and Zhongfu Ye and Rizwan Ullah and Kashif Shabir and Dawei Luo},
	title = {Near Field Source Localization in the Presence of Array Sensor Position Uncertainties},
	journal = {Communications on Applied Electronics},
	issue_date = {November 2016},
	volume = {6},
	number = {3},
	month = {Nov},
	year = {2016},
	issn = {2394-4714},
	pages = {1-6},
	numpages = {6},
	url = {},
	doi = {10.5120/cae2016652437},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


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.


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