A framework for particle filtering in positioning, navigation and tracking problems
Fredrik Gustafsson, Fredrik Gunnarsson, Niclas Bergman, U. Forssell, J. Jansson, P.-J. Nordlund, Rickard Karlsson · 2002
A framework for positioning, navigation and tracking problems using particle filters (recursive Monte Carlo methods) is developed. Automotive and airborne applications, approached in this framework, have proven a numerical advantage over classical Kalman filter based algorithms. Here the use of non-linear measurement models and non-Gaussian measurement noise is the main explanation for the improvement in accuracy, and models for relevant sensors are surveyed.