Content
Lecture:
• Review of some basic nav systems: DME, VOR, GNSS
• Definition of navigation performance parameters: accuracy, integrity, availability and continuity
• Required navigation performance and performance based operation for manned and unmanned aircraft
• Benefits of integrated navigation and sensor fusion
• Basics of estimation theory in the context of navigation
• Linear, Linearized, and Extended Kalman filters (KF, LKF, EKF) and its performance analysis
• Integration mechanizations: DME/DME, DME/INS, GNSS/INS
• Unscented Kalman filter (UKF) and particle filters (PF)
• Laser-based navigation and laser-scan matching
• Visual odometer (VO) and Visual inertial odometer (VIO)
• SLAM, SLAM using EKF and PF, graph-based SLAM
• Occupancy grids
Tutorials:
• Calculate positions using multiple navigation sensors with KF and EKF: DME/INS, GNSS/INS
• Use laser scanners data to estimate change in position
• Integrated laser scanners data with inertial measurements
• Estimate change in position using monocular cameras
• Compute the trajectory and generate a map of the environment at the same time