Paper Info
Title
Comparative Study of Track-to-Track Fusion Methods for Cooperative Tracking with Bearings-only Measurements
Abstract
Using a network of spatially distributed sensors to track a moving object can be a challenging task. In applications with limited communication between sensor nodes and packet loss, it may be impossible to process measurements from these distributed sensor nodes in a central unit. Therefore, it is often necessary to use only the locally available measurements at the sensor nodes and afterwards merge all local tracks into one consistent result. In this paper, several different track-to-track fusion algorithms are compared to cooperatively track a moving object using only bearing measurements. It is shown that the Sample-based Fusion that uses a set of deterministic samples to reconstruct the cross-covariances is a suitable fusion algorithm for the considered setup. Furthermore, it provides the means to efficiently keep track of the cross-covariances between sensor nodes and therefore outperforms conservative methods. The proposed approach is also tested in a real-world indoor localization setup using bearings-only acoustic measurements from three microphone arrays.
Year
DOI
Venue
2019
10.1109/ICPHYS.2019.8780330
2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS)
Keywords
Field
DocType
moving object,distributed sensor nodes,locally available measurements,local tracks,bearing measurements,cross-covariances,real-world indoor localization setup,bearings-only acoustic measurements,track-to-track fusion algorithms,track-to-track fusion methods,microphone arrays,sample-based fusion
Central unit,Packet loss,Fusion,Real-time computing,Kalman filter,Bearing (mechanical),Electronic engineering,Engineering,Merge (version control),Microphone
Conference
ISBN
Citations 
PageRank 
978-1-5386-8501-3
4
0.47
References 
Authors
8
4
Name
Order
Citations
PageRank
Susanne Radtke1111.03
Kailai Li2196.96
Benjamin Noack316823.73
Uwe D. Hanebeck4944133.52