Title: Indoor Navigation Using Wi-Fi Fingerprinting Combined with Pedestrian Dead Reckoning
Author(s): Shan-Jung Yu, Shau-Shiun Jan, David S. De Lorenzo
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 246 - 253
Cite this article: Yu, Shan-Jung, Jan, Shau-Shiun, De Lorenzo, David S., "Indoor Navigation Using Wi-Fi Fingerprinting Combined with Pedestrian Dead Reckoning," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 246-253.
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Abstract: This paper presents a method by which to calibrate the Wi-Fi fingerprinting database with less effort using smartphone based Pedestrian Dead Reckoning (PDR) without any a-priori knowledge. Because the accumulated errors from PDR will decrease the quality of the database, we employ a quaternion based orientation extended Kalman filter (EKF) to deal with the pedestrian heading and to narrow down the PDR positioning error to 2.2 meters for a 270 meter path. Furthermore, we implement the Walkie-Markie method to enhance the accuracy of the PDR step positions used to replace the reference points (RPs) built into the Wi-Fi fingerprinting database. The method defines the Wi-Fi landmarks according to the trend of the Receive Signal Strength (RSS) collected by PDR and converges the pathway map using the Wi-Fi Marks (WMs). In a simulation scenario, the WMs and PDR pathway errors is nearly 0 meters.