Generalized optimal sub-pattern assignment metric
Paper i proceeding, 2017

This paper presents the generalized optimal sub-pattern assignment (GOSPA) metric on the space of finite sets of targets. Compared to the well-established optimal sub-pattern assignment (OSPA) metric, GOSPA is not normalised by the cardinality of the largest set and it penalizes cardinality errors differently, which enables us to express it as an optimisation over assignments instead of permutations. An important consequence of this is that GOSPA allows us to penalize localization errors for detected targets and the errors due to missed and false targets, as indicated by traditional multiple target tracking (MTT) performance measures, in a sound manner. In addition, we extend the GOSPA metric to the space of random finite sets, which is important to evaluate MTT algorithms via simulations in a rigorous way.

Multiple target tracking

optimal sub-pattern assignment metric

metric

random finite sets

Författare

Abu Sajana Rahmathullah

Zenuity

Angel Garcia

Aalto University

Lennart Svensson

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

20th International Conference on Information Fusion, Fusion 2017, Xian, China, 10-13 July 2017

182-189

Ämneskategorier

Reglerteknik

DOI

10.23919/ICIF.2017.8009645

ISBN

978-0-9964-5270-0