Fuzzy Logic Approach to Estimating Tendencies in Target Behavior

Publication Type:

Journal Article


Information & Security: An International Journal, Volume 9, p.58-69 (2002)


attribute data processing, evidence reasoning, Fuzzy Logic, Fuzzy sets


In some real-world situations when kinematic data is not available or it is not sufficient to provide right decisions and/or accurate estimates, estimation schemes may incorporate the attribute data that usually exists simultaneously with kinematic data. However, attribute data is usually incomplete, inconsistent and vague, hence the importance of the problem of overcoming the arising uncertainty in such cases. This paper presents one approach to the estimation of the tendency of target behavior. The authors present an original algorithm for tracking target behavior and evaluate its performance. The algorithm is based on the application of the principles of fuzzy logic to conventional passive radar amplitude measurements. A set of fuzzy models is used to describe alternative tendencies of target behavior. Additionally, a noise reduction procedure is applied. The performance of the developed algorithm in the presence of noise is estimated based on computer simulations results.
Last updated: Wednesday, 13 February 2019