Realtime, Decimeter Accuracy Navigation Using Sliding Window Estimator and Autonomous Vehicle Trajectory Tracking Control
This dissertation focus on achieving high accuracy navigation using low-cost sensors and on high precision trajectory tracking control for Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicles (UAVs).
For high accuracy navigation, this dissertation presents a real-time sliding-window estimator to tightly integrate Differential-GPS (DGPS) and inertial measurement unit (IMU) to achieve reliable, high precision navigation performance in GPS-challenged urban environments using a low-cost, single-frequency (L1) GPS receiver. The approach is novel in that it utilizes the phase measurements, without resolving the integer ambiguity, to improve the accuracy and the robustness of the estimation results. Experimental results demonstrate that the performance of the proposed navigation system is significantly better than the extended Kalman Filter (EKF) (improved by one order of magnitude) and the novel usage of phase measurements further improves the robustness of the estimator to the pseudorange multipath error, which could otherwise be several meters in urban environments.
Regarding precision trajectory tracking, this dissertation presents a new command filtered backstepping technique for under-actuated VTOL UAVs. Quaternions are used to represent the attitude of the vehicle to ensure the global attitude tracking without singularities. Since the quaternions have their own unique algebra, they cannot be filtered by a vector-based command filter; therefore, a second-order quaternion filter is developed to filter the quaternion and automatically compute its derivative, which determines the commanded angular rate vector. A quadrotor vehicle is used as an example to show the performance of the proposed controller.