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Sensors 2017, 17(5), 1020; doi:10.3390/s17051020

Non-Uniform Fusion Tree Generation in a Dynamic Multi-Sensor System

Agency for Defense Development, Yuseong-gu Soonam-dong, Daejeon 34186, Korea
School of Computing, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro Yuseong-gu, Daejeon 34141, Korea
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 26 March 2017 / Revised: 26 April 2017 / Accepted: 1 May 2017 / Published: 4 May 2017
(This article belongs to the Section Sensor Networks)
View Full-Text   |   Download PDF [1754 KB, uploaded 4 May 2017]   |  


This paper addresses the proposal that the number of processed air tracks of a two-tier fusion process can be increased by applying a balanced fusion tree which can balance tracks across local fusion nodes. Every fusion cycle, a fusion process combines duplicate tracks from multiple radars and creates a single integrated air picture (SIAP). The two-tier fusion process divides the fusion process into local and global. The results of the local fusion process, executed at local fusion nodes, are used in the global fusion process. This hierarchical structure can be modeled as a fusion tree: each radar, local fusion node, and the central server is a leaf, internode, and the root, respectively. This paper presents a non-uniform fusion tree generation (NU-FTG) algorithm based on clustering approach. In the NU-FTG, radars with higher scores get more chances to become local fusion nodes. The score of a radar is in proportion to the number of tracks of the radar and its neighbors. All radars execute the NU-FTG independently with the information of their neighbors. Any prior information, such as the appropriate number of local fusion nodes, predefined tree structure, or position of radars, is not required. The NU-FTG is evaluated in the OPNET (Optimized Network Engineering Tool), network simulator. Simulation results show that the NU-FTG performs better than existing clustering methods. View Full-Text
Keywords: air surveillance system; track fusion; multi-sensor tracking; two-tier fusion process; fusion tree; distributed information processing air surveillance system; track fusion; multi-sensor tracking; two-tier fusion process; fusion tree; distributed information processing

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Yeun, K.; Kim, D. Non-Uniform Fusion Tree Generation in a Dynamic Multi-Sensor System. Sensors 2017, 17, 1020.

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