基于流形插值数据库构建的WLAN室内定位算法

doi:10.11999/JEIT161269

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Abstract

To deal with the high cost involved in the location fingerprint database construction due to the dense Reference Points (RPs) distribution and point-by-point Received Signal Strength (RSS) collection in the conventional Wireless Local Area Network (WLAN) indoor localization systems, a new database construction approach based on the integrated semi-supervised manifold learning and cubic spline interpolation is proposed. The proposed approach utilizes a small amount of labeled data and a massive amount of unlabeled data to find the optimal solution to localization target function, and meanwhile relies on the mapping relations between the high-dimensional signal strength space and low-dimensional physical location space to calibrate the unlabeled data with location coordinates. The extensive experiments demonstrate that the proposed approach is able to guarantee the high localization accuracy, as well as significantly reduce the cost involved in location fingerprint database construction.

Key words： Wireless Local Area Network (WLAN) Location fingerprint Semi-supervised learning Manifold alignment Cubic spline interpolation

Received: 24 November 2016 Published: 02 May 2017

PACS:

TN929.5

Fund:

The National Natural Science Foundation of China (61301126), The Program for Changjiang Scholars and Innovative Research Team in University (IRT1299), The Special Fund of Chongqing Key Laboratory (CSTC), Young Scientific Research Program of CUPT (A2013-31)

Corresponding Authors: TANG Yunxia E-mail: 13629735505@139.com

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	ZHOU Mu
	TANG Yunxia
	TIAN Zengshan
	WEI Yacong

Cite this article:

ZHOU Mu,TANG Yunxia,TIAN Zengshan等. WLAN Indoor Localization Algorithm Based on Manifold Interpolation Database Construction[J]. JEIT, 2017, 39(8): 1826-1834.

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http://jeit.ie.ac.cn/EN/10.11999/JEIT161269 OR http://jeit.ie.ac.cn/EN/Y2017/V39/I8/1826

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