关键词: 室内定位, 超宽带, 激光雷达, 数据融合, 粒子滤波

Abstract:

At present, the data fusion of the global navigation satellite system and the light detection and ranging is widely used in the positioning system of autonomous vehicles, but in the indoor environment, the loss of satellite signals leads to low positioning accuracy or even positioning failure. Therefore, a fusion positioning algorithm based on Ultra-Wideband（UWB） and Light Detection and Ranging（LiDAR） is proposed. The algorithm is based on particle filter to solve the location data of two sensors by complementary fusion. The real-time positioning data of UWB is used to improve the positioning speed of LiDAR by providing the range of starting particles. The weight of particles is updated by solving the geometric distance between the LiDAR positioning information and the particles, thereby compensating the positioning error of UWB in a non-line-of-sight environment. An indoor test scene is built, and the fusion positioning algorithm is verified on the smart car platform. The experimental results show that this method is superior to the single sensor positioning scheme of UWB or LiDAR, and the vehicle can still obtain good positioning accuracy and real-time performance when the UWB line of sight is blocked or LiDAR matching fails.

Key words: indoor positioning, ultra-wideband, Light Detection and Ranging（LiDAR）, data fusion, particle filter