Comparative analisis of digital filters for proper positioning of user mobile device using BLE transmitters and multilateration technique

Nowadays, traveling without systems supporting navigation and guidance tothe destination is hard for us to imagine. The outdoor positioning techniques used in thesesolutions have been mastered mainly by global positioning systems. However, assistingthe navigation of users inside large public buildings still needs to be improved. It matterseven more for persons with special needs, such as visually impaired, seniors, or people inwheelchairs. Determining the correct position of the user inside the complex space of amulti-floor building is a big challenge for such persons. Several methods can help in thismatter. For example, technologies such as RFID, WIFI networks, image recognition,or lidar are used. However, the best solution to this problem is using infrastructuresof low energy transmitters (BLE), called beacons. Then, construct an appropriate map to determine the user’s position to help guide the user to a destination. Nevertheless,to designate such a position, we need to know each transmitter’s signal strength andcoordinates. Because of the physical properties of radio waves, the data collected fromsuch transmitters are often inaccurate. This paper compares two methods, the Kalmanfilter and particle filter, to improve the quality of signal strength data received from BLEtransmitters. As a result, the recommendation of the Kalman filter as the best methodto improve the quality of these data and use it in the developed applications supportingindoor navigation in large buildings is provided.