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Conventional single-point-target tracking algorithms are recursive point estimators with point-measurement input data. In less well-known approaches, the tracking algorithm is a recursive set estimator with point-measurement or set-measurement input data.… Click to show full abstract
Conventional single-point-target tracking algorithms are recursive point estimators with point-measurement input data. In less well-known approaches, the tracking algorithm is a recursive set estimator with point-measurement or set-measurement input data. This paper provides a very general, systematic, and theoretically rigorous foundation for Bayes-optimal single-target trackers of the latter kind; as well as specific trackers arising from that foundation. This foundation is intuitive and conceptually simple and, in particular, requires no measure-theoretic complexities.
Journal Title: IEEE Access
Year Published: 2021
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