An Improved Localization Method Using Light Detection and Ranging for Indoor Positionings

This study proposes a low-cost indoor positioning system based on a single Light Detection and Ranging (LiDAR) sensor and several fixed reflective reference points. Distances are obtained by trigonometric measurement, and positions are computed by trilateration. In static tests the average error was 7.4 mm. When the target moves at walking speed, small survey errors of the reference points cause the average error to increase to 21.8 mm. Finally, the proposed Reference Point Update Method (RPUM) that continuously corrects reference point coordinates using a moving average of recent residuals reduces the dynamic error from 208.71 mm to 20.34 mm, which is about 90% improvement. The method used in this paper requires no additional hardware and runs in real time.