Integrating ACC-FMCW Radar for Multi-sensor Navigation in Challenging GNSS Environments
Autonomous vehicles’ positioning and navigation (POS/NAV) systems provide drivers with route guidance information relying mostly on the Global Navigation Satellite Systems (GNSS). The GNSS–based POS/NAV systems suffer from satellite signal blockage, interference and multipath usually experienced by land vehicles in urban areas. The integration with vehicle motion sensors enhances the overall performance for a short period of time. Autonomous land vehicles are now equipped with cameras, radars, and laser ranging devices utilized for blind spot display, collision avoidance, and lane departure warning. The availability of these systems provides an attractive opportunity to increase the POS/NAV system accuracy. This research focuses on the development of an integrated multi-sensor POS/NAV system capable of offering seamless positioning at meter level accuracy for autonomous land vehicles. To bridge the GNSS outages a multi-sensor system utilizing magnetic azimuth from a calibrated magnetometer is developed to enhance the performance of the overall POS/NAV solution by limiting the gyroscope bias drift over time. A new calibration technique is developed to reduce the errors associated with the magnetometer measurements and produce a robust azimuth. Furthermore, a new algorithm is developed to obtain robust positioning information from the adaptive cruise control frequency modulated continuous wave (ACC-FMCW) radar which is used to update the navigation system during GNSS outages. The proposed system is further improved by augmenting magnetic-azimuth update to limit the position drift for long GNSS outages. A further enhancement is added to the system by utilizing fast orthogonal search (FOS) to provide nonlinear error modeling of the residual errors associated with the ACC-FMCW radar positioning solution in order to reduce the error growth over extended and frequent GNSS outages. The proposed system is evaluated on several real road test trajectories involving different types of land vehicles experiencing different motion dynamics. GNSS outages of up to 10 minutes were intentionally introduced to examine the performance. The results show that the proposed method has resulted in a significant performance improvement in the positioning accuracy that can reach more than 80% if compared to the present methods that rely only on integrating the inertial sensor technology with GNSS.