An Online Multisensor Data Fusion Framework for Radar Emitter Classification

Radar emitter classification is a special application of data clustering for classifying unknown radar emitters in airborne electronic support system. In this paper, a novel online multisensor data fusion framework is proposed for radar emitter classification under the background of network centric...

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Bibliographic Details
Main Authors: Dongqing Zhou, Xing Wang, Siyi Cheng, Xi Zhang
Format: Article
Language:English
Published: Wiley 2016-01-01
Series:International Journal of Aerospace Engineering
Online Access:http://dx.doi.org/10.1155/2016/5372510
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Summary:Radar emitter classification is a special application of data clustering for classifying unknown radar emitters in airborne electronic support system. In this paper, a novel online multisensor data fusion framework is proposed for radar emitter classification under the background of network centric warfare. The framework is composed of local processing and multisensor fusion processing, from which the rough and precise classification results are obtained, respectively. What is more, the proposed algorithm does not need prior knowledge and training process; it can dynamically update the number of the clusters and the cluster centers when new pulses arrive. At last, the experimental results show that the proposed framework is an efficacious way to solve radar emitter classification problem in networked warfare.
ISSN:1687-5966
1687-5974