Multitarget Bayes filtering via first-order multitarget moments

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Summary

Recursion Bayes filter equations for the probability hypothesis density are derived that account for multiple sensors, nonconstant probability of detection, Poisson false alarms, and appearance, spawning, and disappearance of targets and it is shown that the PHD is a best-fit approximation of the multitarget posterior in an information-theoretic sense.

Type
article
Published
2003-10-01
Cited by
2,281
References
41

Keywords

Moment (physics), Kalman filter, Bayes' theorem, Filter (signal processing), Mathematics

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