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An Implementation of the Poisson Multi-Bernoulli Mixture Trajectory Filter via Dual Decomposition
- Publication Year :
- 2018
-
Abstract
- This paper proposes an efficient implementation of the Poisson multi-Bernoulli mixture (PMBM) trajectory filter. The proposed implementation performs track-oriented N-scan pruning to limit complexity, and uses dual decomposition to solve the involved multi-frame assignment problem. In contrast to the existing PMBM filter for sets of targets, the PMBM trajectory filter is based on sets of trajectories which ensures that track continuity is formally maintained. The resulting filter is an efficient and scalable approximation to a Bayes optimal multi-target tracking algorithm, and its performance is compared, in a simulation study, to the PMBM target filter, and the delta generalized labelled multi-Bernoulli filter, in terms of state/trajectory estimation error and computational time.<br />Comment: 8 pages, 2018 21st International Conference on Information Fusion (FUSION)
- Subjects :
- Electrical Engineering and Systems Science - Signal Processing
Subjects
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.1811.12281
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.23919/ICIF.2018.8455236