基于UKF的UWB和GPS融合定位算法

智能汽车的发展对高精度定位需求日益显现. 针对汽车在城市建筑群、立交桥等特定环境下, 可见GPS卫星数量下降、车载GPS和惯性测量单元(inertial measurement unit, IMU)组合定位系统中IMU产生积累误差导致不能精确定位问题, 本文提出一种基于无迹卡尔曼滤波(unscented Kalman ...

Fusion Positioning Algorithm of UWB and GPS Based on UKF

The demand of intelligent vehicles for high-precision positioning is increasingly strong. In complex environments of urban buildings, overpasses, and so on, the number of visible GPS satellites decreases and the inertial measurement unit (IMU) in a fusion positioning system of the vehicle GPS andthe IMU produces a time accumulation error, leading to inaccurate positioning. This paper proposes a fusion positioning algorithm of an ultra wide band (UWB) and a GPS based on the unscented Kalman filter (UKF). The system architecture scheme is constructed. The data analysis algorithm for the UWB module is optimized, and the model of a nonlinear fusion positioning system of a UWB and a GPS is built. The complexity of the algorithm is analyzed, and the algorithm is written into the controller for real-time filtering. The noise error and variance of different algorithms are analyzed. The experiments show that the fusion positioning algorithm of a UWB and a GPS based on the unscented Kalman filter, with good real-time performance, high solution accuracy, and no filter divergence, can meet the needs of high-precision positioning of vehicles in complex urban environments.