Course title

Course code


Introduction to Inertial and Multi-Sensor Navigation


Introduction to inertial sensors, operating principle of inertial sensors, observations and types. Brief introduction of coordinate frames used by inertial sensors. Allan variance and performance quantification of inertial sensors. State space model, measurement model, smoothing, filtering, sstimation theory: Least squares, sequential least squares, Kalman filter, extended Kalman filter, unscented Kalman Filter

Introduction to inertial navigation, kinematic navigation equations, IMU/AHRS/INS, INS errors and propagation. INS/GNSS integration approaches: Loosely coupled, tightly coupled, ultra-tightly coupled,

overview of other sensors and integration approaches for navigation in indoor/outdoor environments: ultra-wide-band, Wi-Fi, LiDAR. Brief overview of centralized cooperative localization



  1. Grewal, M. S., Andrews, A. P., Bartone, C. G. (2013). Global Navigation Satellite Systems, Inertial Navigation, and Integration. 3rd ed. John Wiley and Sons Inc.
  2. Groves, P. D. (2013). Principles of GNSS, inertial and multi-sensor integrated navigation systems. 2nd ed. Artech House.
  3. Simon, D. (2006). Optimal State Estimation: Kalman, H Infinity,and Nonlinear Approaches. 1st ed. Wiley-Interscience.