Algorithm Design for a Low-Cost Vehicle Integrated Navigation System in the GPS Outage

The performance of a micro-electro-mechanical system-inertial measurement unit (MEMS-IMU)/global positioning system (GPS) integrated system will be degraded significantly due to the poor performance of the MEMS-IMU if the GPS signals are blocked by the buildings. To resolve this problem, the up and side vehicle velocity constraints are modelled as the virtual measurements. The nonlinear velocity measurement equations are derived without the small angle approximation if the nonlinearity due to the low accuracy of the MEMS IMU is taken into account in the GPS outage. The Unscented Kalman Filter (UKF) is employed to improve the integration accuracy. The vehicle test results show that the proposed nonlinear algorithm with the velocity constrains can improve the integration accuracy significantly in the GPS outage and converge quickly when the GPS signals is reacquired.