An Integrated Navigation System Using GPS and Low-Cost Vehicle Dynamic Sensors

The aim of this paper is to present a novel integrated navigation system, based on the fusion between the Global Positioning System (GPS) and low-cost vehicle onboard dynamic sensors for autonomous vehicle positioning problems. In this system, the information of vehicle’s angular rotation is applied to dead reckoning (DR) module based on the Unscented Kalman Filter (UKF) to provide the vehicle position information during GPS outage. In the DR module based on UKF, vehicle onboard dynamic sensors, include wheels speed sensors, accelerometer, and steering angle sensor, are utilized to estimate the vehicle yaw rate, while the traditional method using IMU sensor is relatively expensive. Also, the vehicle dynamic model is employed in the estimation of yaw rate, which can provide better accuracy than the traditional kinematic model. To validate the effectiveness of the integrated navigation system, tests are carried out on a small-scale vehicle platform. The test results show that the yaw rate could be well estimated and the integrated navigation system using low-cost sensors could also keep the error distance in a small range.