Comparative Analisis of Digital Filters for Proper Positioning of User Mobile Device Using BLE Transmitters and Multilateration Technique

Abstract

Nowadays, traveling without systems supporting navigation and guidance to the destination is hard for us to imagine. The outdoor positioning techniques used in these solutions have been mastered mainly by global positioning systems. However, assisting the navigation of users inside large public buildings still needs to be improved. It matters even more for persons with special needs, such as visually impaired, seniors, or people in wheelchairs. Determining the correct position of the user inside the complex space of a multi-floor building is a big challenge for such persons. Several methods can help in this matter. For example, technologies such as RFID, WIFI networks, image recognition, or lidar are used. However, the best solution to this problem is using infrastructures of 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 and coordinates. Because of the physical properties of radio waves, the data collected from such transmitters are often inaccurate. This paper compares two methods, the Kalman filter and particle filter, to improve the quality of signal strength data received from BLE transmitters. As a result, the recommendation of the Kalman filter as the best method to improve the quality of these data and use it in the developed applications supporting indoor navigation in large buildings is provided.