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.