Abstract: Multitarget-multisensor tracking systems consist of data correlation and state estimation. The multitarget tracking is made interesting by the data association problem. The data correlation and state estimation are both certainly independent and closely relative, but the performance of tracking systems can be improved by suitable incorporating the two components. In this paper, a fuzzy correlation approach is presented based on fuzzy clustering means algorithm with Mahalanobis distance. The approach, in a sense, fuses two different procedures of data correlation and state estimation. The simulation result using Monte Carlo method is given to demonstrate the efficiency of the new approach.