Estimation and Control of a Multi-Vehicle Testbed Using GPS Doppler Sensing

This thesis presents estimation and control algorithms used to coordinate a multivehicle testbed. A total sensor package using the Global Positioning System as the primary sensor with secondary inertial sensors for when GPS is not available and a single point position fix measurement is designed. A new method of integrated velocity estimation is presented using only the Doppler measurements provided by the GPS NAVSTAR constellation. This shows significant improvement on previously used velocity integration methods by elminating unmodeled sensor biases. Furthermore, the algorithm includes the ability to calibrate inertial sensor biases in real-time, which are then used when observability to the constellation is blocked. The single point position fix is able to determine the initial position of the estimation or reset position estimation error drift. Methods are also presented for doing the low-level velocity and heading control of the test vehicle as well as nonlinear closed-loop path following control. Results of multiple estimation algorithms are presented showing that position accuracy with integrated velocity from a coupled GPS/INS/postion fix package is on the order of 10–30 cm over elapsed time of 2–3 minutes. While these errors are larger than CDGPS, the values are lower than typically available from absolute or differential Code phase, and this approach does not have the additional complexity of solving the CDGPS biases. Experiments also demonstrate the robustness and reliability of the path following algorithm. The designed testbed therefore has the necessary estimation and control capability to complete hardware-in-the-loop path following experiments. Thesis Supervisor: Jonathan P. How Title: Associate Professor