An estimator based on fuzzy if-then rules for the multisensor multidimensional multitarget tracking problem
Chin‐Wang Tao, J.S. Taur, Han-Lung Kuo, J.C. Wu, Wiley E. Thompson · 1994
In this paper, an estimator based on fuzzy if-then rules are developed for multidimensional multitarget tracking with multisensor data taken in a cluttered environment. The clustering algorithm based upon a pseudo k-means algorithm and the match-agreement data technique designed in our previous paper are used here for clustering multisensor data from a clustered environment and data association problem in multitarget tracking. The estimator based on fuzzy if-then rules consists of Gaussian membership functions, min- "and" inference, and centroid defuzzification. Examples are presented to illustrate the comparisons between a Kalman estimator and the fuzzy estimator.>