Ues of Vision Sensors and Lane Maps to Aid GPS-INS Navigation

Abstract

This thesis proposes a method to increase observability of a GPS/INS system operating under limited satellite coverage. Measurements from vision sensors are used to supplement the GPS pseudorange and pseudorange-rate measurements. Both LiDAR and camera measurements are used to measure the lateral position of a vehicle in its current lane. The vision measurements provide local based positioning based off the lane. A map of the lane is used to relate the local position measurement provided by the vision systems to the global coordinate frame used by GPS and the navigation filter. Since the filter is used for ground vehicles, the height above the ground is constant. The constant height can be used to constrain position in another axis that is orthogonal to the axis in which lane position measurements are given.

In order to test the performance of the navigation filter, real data from the NCAT test track in Opelika, Alabama will be used. RTK GPS is used as a "truth" metric in order to determine filter performance. Experimental results show that using vision measurements with a precise lane map results in centimeter level global accuracy in the axis perpendicular to the road and meter level (depending on the quality of GPS measurements available) global accuracy in the axis parallel with the road. It is also shown that the navigation filter remains observable and functional if two GPS observations along with vision measurement and a lane map are available. The results also show a reduction in position drift when GPS is unavailable if vision measurements and a lane map are available.