An Online Multisensor Data Fusion Framework for Radar Emitter Classification

Joint Authors

Zhou, Dongqing
Wang, Xing
Cheng, Siyi
Zhang, Xi

Source

International Journal of Aerospace Engineering

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-16, 16 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-05-30

Country of Publication

Egypt

No. of Pages

16

Abstract EN

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.

American Psychological Association (APA)

Zhou, Dongqing& Wang, Xing& Cheng, Siyi& Zhang, Xi. 2016. An Online Multisensor Data Fusion Framework for Radar Emitter Classification. International Journal of Aerospace Engineering،Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1105005

Modern Language Association (MLA)

Zhou, Dongqing…[et al.]. An Online Multisensor Data Fusion Framework for Radar Emitter Classification. International Journal of Aerospace Engineering No. 2016 (2016), pp.1-16.
https://search.emarefa.net/detail/BIM-1105005

American Medical Association (AMA)

Zhou, Dongqing& Wang, Xing& Cheng, Siyi& Zhang, Xi. An Online Multisensor Data Fusion Framework for Radar Emitter Classification. International Journal of Aerospace Engineering. 2016. Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1105005

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1105005