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Article

iBeacon Indoor Positioning Method Combined with Real-Time Anomaly Rate to Determine Weight Matrix

Civil Engineering College, Nanjing Forestry University, Nanjing 210037, China
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Author to whom correspondence should be addressed.
Sensors 2021, 21(1), 120; https://doi.org/10.3390/s21010120
Received: 27 November 2020 / Revised: 19 December 2020 / Accepted: 23 December 2020 / Published: 27 December 2020
(This article belongs to the Section Intelligent Sensors)
This paper proposes an indoor positioning method based on iBeacon technology that combines anomaly detection and a weighted Levenberg-Marquadt (LM) algorithm. The proposed solution uses the isolation forest algorithm for anomaly detection on the collected Received Signal Strength Indicator (RSSI) data from different iBeacon base stations, and calculates the anomaly rate of each signal source while eliminating abnormal signals. Then, a weight matrix is set by using each anomaly ratio and the RSSI value after eliminating the abnormal signal. Finally, the constructed weight matrix and the weighted LM algorithm are combined to solve the positioning coordinates. An Android smartphone was used to verify the positioning method proposed in this paper in an indoor scene. This experimental scenario revealed an average positioning error of 1.540 m and a root mean square error (RMSE) of 1.748 m. A large majority (85.71%) of the positioning point errors were less than 3 m. Furthermore, the RMSE of the method proposed in this paper was, respectively, 38.69%, 36.60%, and 29.52% lower than the RMSE of three other methods used for comparison. The experimental results show that the iBeacon-based indoor positioning method proposed in this paper can improve the precision of indoor positioning and has strong practicability. View Full-Text
Keywords: indoor positioning; iBeacon-based positioning; anomaly detection; isolation forest; Levenberg-Marquadt indoor positioning; iBeacon-based positioning; anomaly detection; isolation forest; Levenberg-Marquadt
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MDPI and ACS Style

Guo, Y.; Zheng, J.; Zhu, W.; Xiang, G.; Di, S. iBeacon Indoor Positioning Method Combined with Real-Time Anomaly Rate to Determine Weight Matrix. Sensors 2021, 21, 120. https://doi.org/10.3390/s21010120

AMA Style

Guo Y, Zheng J, Zhu W, Xiang G, Di S. iBeacon Indoor Positioning Method Combined with Real-Time Anomaly Rate to Determine Weight Matrix. Sensors. 2021; 21(1):120. https://doi.org/10.3390/s21010120

Chicago/Turabian Style

Guo, Yu, Jiazhu Zheng, Weizhu Zhu, Guiqiu Xiang, and Shaoning Di. 2021. "iBeacon Indoor Positioning Method Combined with Real-Time Anomaly Rate to Determine Weight Matrix" Sensors 21, no. 1: 120. https://doi.org/10.3390/s21010120

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