2019_programme: DISTRIBUTED FUSION IN UNDERWATER SENSOR NETWORKS: FUSING BEARING INFORMATION
- Session: 19. Situation-adaptive distributed networked systems
Organiser(s): Ehlers Frank, Schulz Arne
- Lecture: DISTRIBUTED FUSION IN UNDERWATER SENSOR NETWORKS: FUSING BEARING INFORMATION [invited]
Paper ID: 870
Author(s): Otnes Roald, Zetterberg Per, Blouin Stephane, Nordenvaad Magnus Lundberg, Austad Håvard, Dombestein Elin
Presenter: Otnes Roald
Presentation type: oral
Abstract: In underwater sensor networks, distributed data fusion may be more efficient than centralized fusion because the limited data transmission capacity can make it difficult to collect all required sensor information at a centralized fusion centre. In this paper, we investigate three distributed fusion techniques applied to a network of passive acoustic underwater sensor nodes. We focus on the process of having a node combining its own bearing-to-target information with bearing-to-target information received from another node. In one of the techniques, we approximate the uncertainty in crossfixes in Cartesian coordinates by a Gaussian distribution with their second-order statistics derived from an exact distribution. The bearings and covariance matrixes are fed into a Kalman filter for tracking. The other methods are a particle filter using an exact distribution, and a distributed particle filter using an approximate likelihood representation. The performance of the methods is investigated on simulated data as well as on real-world data collected by seafloor sensor nodes during a Stockholm Archipelago sea trial in the trilateral collaborative project DUSN (Distributed Underwater Sensor Networks) between Canada, Norway, and Sweden.
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- Corresponding author: Dr Otnes Roald
Affiliation: Norwegian Defence Research Establishment (FFI)
Country: Norway
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