Performance evaluation of multi-bernoulli conjugate priors for multi-target filtering
Paper in proceedings, 2017

In this paper, we evaluate the performance of labelled and unlabelled multi-Bernoulli conjugate priors for multi-target filtering. Filters are compared in two different scenarios with performance assessed using the generalised optimal sub-pattern assignment (GOSPA) metric. The first scenario under consideration is tracking of well-spaced targets. The second scenario is more challenging and considers targets in close proximity, for which filters may suffer from coalescence. We analyse various aspects of the filters in these two scenarios. Though all filters have pros and cons, the Poisson multi-Bernoulli filters arguably provide the best overall performance concerning GOSPA and computational time.

Author

Yuxuan Xia

Chalmers, Signals and Systems

Karl Granström

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Lennart Svensson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Angel Garcia

Aalto University

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

644-651

Subject Categories

Communication Systems

DOI

10.23919/ICIF.2017.8009710

ISBN

978-0-9964-5270-0

More information

Latest update

3/19/2018