Research of Covariance Intersection Algorithm Based on Unscented Transformatio

In view of problems existed in data fusion of distributed data observation system, namely bigger error in data linearization process and uncorrecting error in filtering process, the paper proposed a covariance intersection algorithm based on unscented transformation. The algorithm makes unscented transformation for system's data at first, then uses covariance intersection algorithm to filter data, which can gain better filtering performance. The experiment result showed that the algorithm makes up deficiencies of covariance intersection algorithm and can correct errors produced in processes of data linearization and filtering, which is an effective data fusion algorithm.