Abstract

In this paper, a fuzzy logic data correlation approach for multisensor–multitarget tracking is proposed. This fuzzy correlation approach is developed based on fuzzy clustering means algorithm. The proposed approach is applied to a two- and a four-dimensional multisensor–multitarget tracking system using Monte Carlo simulations. Fuzzy system performance evaluation is presented to demonstrate the efficiency of the new approach. The computational complexity of this approach is also analyzed and compared to that of conventional fuzzy logic data association methods. Considerable improvement in terms of computational complexity and performance is achieved.

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