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Backward Simulation for Sets of Trajectories

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Document pages: 10 pages

Abstract: This paper presents a solution for recovering full trajectory information,via the calculation of the posterior of the set of trajectories, from asequence of multitarget (unlabelled) filtering densities and the multitargetdynamic model. Importantly, the proposed solution opens an avenue of trajectoryestimation possibilities for multitarget filters that do not explicitlyestimate trajectories. In this paper, we first derive a general multitrajectoryforward-backward smoothing equation based on sets of trajectories and therandom finite set framework. Then we show how to sample sets of trajectoriesusing backward simulation when the multitarget filtering densities aremulti-Bernoulli processes. The proposed approach is demonstrated in asimulation study.

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