Nonlinear Estimation and Multiple Sensor Fusion Using Unscented Information Filtering

Abstract

This letter represents a new unscented information filtering algorithm for nonlinear estimation and multiple sensor information fusion. The proposed information fusion algorithm is derived by embedding the unscented transformation method used in the sigma point filter into the extended information filtering architecture. The new information 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. Performance comparison of the proposed filter with the extended information filter is demonstrated through a target-tracking simulation study.