Distributed Filtering Using Set Models With Confidence Values

This paper describes an algorithm of distributed filtering using set models with confidence values. No statistics of noise distribution are needed. The only information required is the sets with confidence values from which the modeling and measurement errors and the initial values are obtained. Therefore, the algorithm has great potential for real-world applications.