Thesis is based on three different aspects of Kalman filtering.
>Kalman filters for navigation. Investigate the difference between a Extended Kalman Filter and a Linearized Kalman Filter with feedback. And show how different system models relate to these Kalman Filters when implemented in a filter.
>Smoothing. Investigate how much there is to be gained from smoothing. We will only look at the fixed-interval smoother, using the method of forward and backward filtering.
>The Covariance Analysis Program. Designing a program that handles the theory of covariance analysis, which gives us the ability to compare system model design and performance.