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Sensors 2018, 18(1), 318; https://doi.org/10.3390/s18010318

EKF–GPR-Based Fingerprint Renovation for Subset-Based Indoor Localization with Adjusted Cosine Similarity

School of Electronic and Information, Northwestern Polytechnical University, Xi’an 710072, China
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Received: 27 December 2017 / Revised: 18 January 2018 / Accepted: 21 January 2018 / Published: 22 January 2018
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Abstract

Received Signal Strength Indicator (RSSI) localization using fingerprint has become a prevailing approach for indoor localization. However, the fingerprint-collecting work is repetitive and time-consuming. After the original fingerprint radio map is built, it is laborious to upgrade the radio map. In this paper, we describe a Fingerprint Renovation System (FRS) based on crowdsourcing, which avoids the use of manual labour to obtain the up-to-date fingerprint status. Extended Kalman Filter (EKF) and Gaussian Process Regression (GPR) in FRS are combined to calculate the current state based on the original fingerprinting radio map. In this system, a method of subset acquisition also makes an immediate impression to reduce the huge computation caused by too many reference points (RPs). Meanwhile, adjusted cosine similarity (ACS) is employed in the online phase to solve the issue of outliers produced by cosine similarity. Both experiments and analytical simulation in a real Wireless Fidelity (Wi-Fi) environment indicate the usefulness of our system to significant performance improvements. The results show that FRS improves the accuracy by 19.6% in the surveyed area compared to the radio map un-renovated. Moreover, the proposed subset algorithm can bring less computation. View Full-Text
Keywords: indoor localization; RSSI; fingerprint; Extended Kalman Filter; Gaussian Process Regression; adjusted cosine similarity indoor localization; RSSI; fingerprint; Extended Kalman Filter; Gaussian Process Regression; adjusted cosine similarity
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Yang, J.; Li, Y.; Cheng, W.; Liu, Y.; Liu, C. EKF–GPR-Based Fingerprint Renovation for Subset-Based Indoor Localization with Adjusted Cosine Similarity. Sensors 2018, 18, 318.

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