Map-Aided Indoor Positioning Algorithm with Complex Deployed BLE Beacons

As communication technology and smartphones develop, many indoor positioning applications based on Bluetooth low energy (BLE) beacons have emerged. However, in a complex BLE network, it can be challenging to select the optimal reference beacon, and accurate positioning becomes difficult. Fortunately, if the BLE network is displayed on a map, we can intuitively grasp the structure and density of the beacons in each area, which is important information for accurate positioning. Therefore, in this study we developed a map-aided indoor positioning algorithm to model the relationship between beacons in the positioning area in a parking lot. Specifically, the algorithm split all beacons into multiple cell areas to find the optimal reference beacon in that area. Then, the optimal reference beacon is used to find the preferred reference beacons among the real-time beacons. Finally, the positioning results were calculated and evaluated according to the preferred beacons. According to the results, our method can optimize the selection of reference beacons in different areas. The average positioning accuracy was 2.09 m and the results can be scored accurately. The results verify that our algorithm can effectively use map information to guide the selection of reference beacons in complex environments.