PP algorithm for Particle Filtering within Ellipsoidal Regions

Abstract

The paper introduces a new estimation algorithm that blends together particle filtering techniques and set-membership theory to provide more complete and reliable state estimates. The algorithm is applied to linear time-discrete dynamic systems where the process and the measurement noises are combined with model uncertainties through ellipsoidal constraints; the algorithm however can be extended as well to mild non linear systems by replacing nonlinearities with uncertainties in the system matrices. Each step of the proposed estimation method is described in detail, and some simulation results are provided to show the behaviour of the algorithm.