Location Estimation Method of Positioning System utilizing the iBeacon

Namgung, Hyun; Lim, Il-Kwon; Lee, Jae-Kwang

doi:10.6109/jkiice.2015.19.4.925

Cited by 6 publications

(1 citation statement)

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“…However, in the case of a BLE terminal, it is difficult to calculate the distance based on the RSSI value because of the large RSSI deviation. (7,8) In other research, the location of the terminal was measured by dividing it into units of a certain distance. To reduce the collected RSSI noise, preprocessing is performed using an extended Kalman filter and a signal stabilization filter.…”

Section: Introductionmentioning

confidence: 99%

Improved Method of Bluetooth-low-energy-based Location Tracking Using Neural Networks

Youm¹,

Shin²

2021

Sensors and Materials

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Indoor positioning and tracking technology perform important functions in augmented reality, smart factories, and autonomous driving. The indoor positioning method using a Bluetooth low energy (BLE) beacon has been considered challenging, owing to the deviation of the receiver signal strength indicator (RSSI) value. In this paper, we propose an indoor location tracking method by adding an algorithm to reduce differences between the actual and predicted locations of moving objects. By using synthetic data generated from actual measured values, neural networks were trained and used to predict the location of the beacon. Also, an improved tracking algorithm of moving objects was proposed by considering the angle of rotation relative to the origin. Through the simulation, it was confirmed that the improved tracking results were obtained by applying the proposed tracking algorithm to the locations predicted by neural networks. Eliminate θ i in temp_angle [1:k] endif endfor Copy temporary array temp_angle [1:k] to valid angle array valid_angle[1:k] Obtain θ e from the mean of valid_angle[1:k] Sleep for a second endwhile About the Authors Sungkwan Youm received his B.S. degree in control instrumentation engineering from

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Section: Introductionmentioning

confidence: 99%