Unscented Information Filtering for Distributed Estimation and Multiple Sensor Fusion

Abstract

This paper represents distributed estimation and multiple sensor information fusion using an unscented information flltering algorithm. The proposed information fusion algorithm is developed by embedding the unscented transformation method used in the sigma point fllter into the extended information flltering architecture, and its algorithm is further extended for distributed estimation in hierarchical sensor networks. The new information fusion fllter achieves not only the accuracy and robustness of the sigma point fllter, but also the ∞exibility of the information fllter for multiple sensor estimation in distributed sensing networks. Performance comparison of the proposed sensor fusion fllter with the extended information fllter is demonstrated through a simple target-tracking simulation study.