Preliminary study for improving accuracy on Indoor positioning method using compass and walking detect
Indoor positioning technology is commercially available now, however, the positioning accuracy is not sufficient in the current technologies. Currently available indoor positioning technologies differ in terms of accuracy, costs and effort, but have improved quickly in the last couple of years. It has been actively conducted research for estimating indoor location using RSSI (Received Signal Strength Indicator) level of Wi-Fi access points or BLE (Bluetooth Low Energy) tags. WiFi signal is commonly used for the indoor positioning technology. However, It requires an external power source, more setup costs and expensive. BLE is inexpensive, small, have a long battery life and do not require an external energy source. Therefore, using BLE tags we might be able to make the positioning system practical and inexpensive way. In this paper, we investigate such practical type of indoor positioning method based on BLE. BLE RSSI are processed by Multilayer Perceptron(MLP). Also, compass data and walking speed estimation with an extended Kalman filter is used to improve the accuracy. Our preliminary experimental result shows 2.21m error in case of the MLP output. In preliminary experimental results, the proposed approach improved the accuracy of indoor positioning by 21.2%.
Keywords:indoor positioning BLE fingerprint Extended Kalman filter
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