Fuzzy Data Association Filter (FDAF) For Maneuvering Multitarget Tracking. | ||||
| International Conference on Aerospace Sciences and Aviation Technology | ||||
| Article 68, Volume 10, 10th International Conference On Aerospace Sciences & Aviation Technology, May 2003, Page 985-999 PDF (2 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/asat.2013.24720 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| ASHRAF M. ANWAR1; AHMED A. BAHNASAWI2 | ||||
| 1Graduate student, Dpt. Of Elect. and Comm., M.T.C, Cairo, Egypt. | ||||
| 2Professor, Dpt. Of Elect. and Comm., Fac. Of Eng. Cairo University, Guiza, Egypt. | ||||
| 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. | ||||
| Keywords | ||||
| data association; tracking systems; Fuzzy Logic; multisensor multitarget tracking; intelligent tracking | ||||
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