5 July 1995 Distributed multisensor multitarget tracking algorithm
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Abstract
In this paper, an efficient distributed multi-sensor multi-target tracking algorithm is proposed. This distributed tracker consists of two main components: local sensor-level trackers and a track fuser. In the track fuser, track data from local sensors are first transformed to a common coordinate, and synchronized using a linear Kalman filter. A sequential minimum normalized distance nearest neighbor correlation and minimum mean-square error fusion algorithm, combined with the majority decision making logic is presented to correlate and fuse tracks from different sensors. Simulated data under various tracking conditions are used to evaluate the feasibility and effectiveness of this new distributed tracker.
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Ying Zhang, Henry Leung, Titus K. Y. Lo, John Litva, "Distributed multisensor multitarget tracking algorithm", Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); doi: 10.1117/12.213010; https://doi.org/10.1117/12.213010
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