A Fast and Resource Efficient Method for Indoor Positioning Using Received Signal Strength

Document Type

Article

Publication Date

12-1-2016

Publication Title

IEEE Transactions on Vehicular Technology

Volume

65

Issue

12

First Page

9747

Keywords

Indoor localization, received signal strength, support vector machines (SVMs), undersampling, wireless local area network (WLAN)

Last Page

9758

Abstract

This paper proposes an indoor localization method using online independent support vector machine (OISVM) classification method and undersampling techniques. The system is based on the received signal strength indicator (RSSI) of Wi-Fi signals. A new undersampling algorithm is developed to address the imbalanced data problem associated with the OISVM, and a kernel function parameter selection algorithm is introduced for the training process. The time complexity of both the training process and the prediction process are significantly decreased. Comparative experimental results indicate that the training speed and the prediction speed are improved by at least ten and five times, respectively. Furthermore, through online learning, the estimation error is decreased by 0.8 m. Such an improvement makes the proposed method an ideal indoor positioning solution for portable devices for which the processing power and the memory are limited.

DOI

10.1109/TVT.2016.2530761

ISSN

00189545

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