This course examines current navigation systems. Focussing specifically on inertial and GPS sensors it initially explores how these sensors work, and the requirements levied on navigation systems. The course then delves into the techniques that are used to improve navigation performance in the face of noise and bias in several inputs. These techniques employ the class of estimation algorithms known as Kalman filters and extended Kalman filters. The course provides an in-depth introduction into these techniques and is supported by appropriate laboratory and simulation exercises to illustrate the behaviour or application of each system or technique. The course concludes by examining the benefits that estimation techniques provide in real world systems.