Closely Coupled GPS/INS Relative Positioning For Automated Vehicle Convoys

Abstract

In this thesis, differential GPS methods are developed for use in automated vehicle convoy positioning. The GPS pseudorange and carrier phase measurements are used to compute relative position vectors between two vehicles with sub-meter errors. It is the carrier phase measurement that makes this level of accuracy attainable but the carrier phase ambiguity must be resolved prior to the relative position estimation. An algorithm, referred to as Dynamic base Real Time Kinematic (DRTK) algorithm, is described in this thesis to estimate the carrier phase ambiguity and the relative position vector between two GPS receivers. The DRTK algorithm is capable of using single frequency (L1 or L2 frequency only) or dual frequency (L1 and L2 frequency) GPS measurements to estimate the relative position vector. A comparative study of the performance of the algorithm using either single or dual frequency measurements is presented.

The DRTK algorithm is expanded to incorporate inertial measurement to increase to output rate, to improve solution availability, and to improve the reliability of the algorithm. Since inertial navigation systems (INS) compute a navigation solution independent of any additional infrastructure, the INS can be used to update the relative position vector estimate during short GPS outages. The update rate of the INS is also as much as ten times the rate of the GPS receiver meaning that the integrated system produces estimates at a significantly higher output rate. The combined DRTK/INS system is implemented with two integration architectures -- a federated GPS/INS/DRTK architecture and a centralized DRTK/INS architecture. Each configuration produced estimates of the relative position vector with error on the centimeter level.

Finally, the use of relative positioning to autonomously follow a human driven lead vehicle is presented. Time difference carrier phase (TDCP) measurements are used to estimate the change in the position of the following vehicle between measurement epochs. The TDCP algorithm is combined with the DRTK algorithm to estimate the position of the following vehicle relative to a virtual lead vehicle position. Analysis of the accuracy of the TDCP algorithm at individual measurement epochs and over varying time intervals is presented. The DRTK/TDCP following method is compared to a GPS waypoint following method using data collected on an automated all-terrain vehicle.