Shooting two birds with two bullets: how to find Minimum Mean OSPA estimates
Paper i proceeding, 2010

Most area-defense formulations follow from the assumption that threats must first be identified and then neutralized. This is reasonable, but inherent to it is a process of labeling: threat A must be identified and then threat B, and then action must be taken. This manuscript begins from the assumption that such labeling (A & B) is irrelevant. The problem naturally devolves to one of Random Finite Set (RFS) estimation: we show that by eschewing any concern of target label we relax the estimation procedure, and it is perhaps not surprising that by such a removal of constraint (of labeling) performance (in terms of localization) is enhanced. A suitable measure for the estimation of unlabeled objects is the Mean OSPA (MOSPA). We derive a general algorithm which provided the optimal estimator which minimize the MOSPA. We call such an estimator a Minimum MOSPA (MMOSPA) estimator.

Författare

Marco Guerriero

Lennart Svensson

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Daniel Svensson

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

P. Willett

Proceedings of the 13th International Conference on Information Fusion

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Sannolikhetsteori och statistik

Signalbehandling

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2017-10-07