Robust Estimation for Discrete-Time Markovian Jump Linear Systems in a Data Fusion Scenario

Abstract

This paper considers the problem of robust recursive estimation for discrete-time Markovian jump linear systems in both weighted and probabilistic data fusion scenarios. The problem is stated in terms of the optimization of an appropriate quadratic functional in a data fusion scenario. The estimates presented here were developed based on systems with more than one measurement equation. Numerical examples are presented to verify the effectiveness of proposed algorithms.

Keywords

• Markovian Systems
• Data Fusion
• Robustness
• Kalman Filter