Abstract
This paper presents a new algorithm for Manoeuvring Multitarget Tracking. The suggested algorithm solves the interrelated tasks of data association and state estimation in one combined algorithm. The new algorithm is based on fuzzy cluster means algorithm to solve the data association problem, and an adaptive Kalman filter for maneuvering multitaget tracking. To demonstrate the effectiveness of the proposed algorithm to perform data association and state estimation in multitarget tracking in high noisy measurement, an example of four-dimensional tracking system is considered. A scenario of two targets moving together at near distance and then making high maneuver is considered. The performance is evaluated using Monte Carlo simulations and the results are reasonable.
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