Dynamic Information Fusion with the Integration of Local Observers, Value of Information, and Active-Passive Consensus Filters
This paper proposes a dynamic information fusion framework for sensor networks with the integration of local observers, value of information, and active-passive consensus filters as well as a layer to monitor the validity of information. Specifically, we consider a process of interest consisting of multiple subprocesses (for example, multiple targets to be monitored). The heterogeneity in the sensor networks is considered and handled in many aspects such as nodes are allowed to have different sensing capabilities, different information node roles (active and/or passive; that is, a node can be subject to observations of the process or to no observation), and different weights on information (value of information). In addition, the information validity monitor layer allows operators to evaluate the reliability of the fused information based on the local feedbacks received from the sensor network. Several illustrative numerical examples are also presented to illustrate the efficacy and discuss the practical aspects of the proposed dynamic information fusion framework.
D. Tran et al., "Dynamic Information Fusion with the Integration of Local Observers, Value of Information, and Active-Passive Consensus Filters," Proceedings of the AIAA Scitech 2019 Forum (2019, San Diego, CA), American Institute of Aeronautics and Astronautics (AIAA), Jan 2019.
The definitive version is available at https://doi.org/10.2514/6.2019-2262
AIAA Scitech 2019 Forum (2019: Jan. 7-11, San Diego, CA)
Mechanical and Aerospace Engineering
Electrical and Computer Engineering
Intelligent Systems Center
Keywords and Phrases
Aviation; Information fusion; Sensor networks; Sensor nodes; Consensus filter; Dynamic information; Information nodes; Multiple targets; Value of information; Passive filters
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2019 American Institute of Aeronautics and Astronautics (AIAA), All rights reserved.
01 Jan 2019