Unscented information filtering for distributed estimation and multiple sensor fusion

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