文献详情
Specific emitter identification for satellite communication using probabilistic neural networks
文献类型：期刊
通讯作者：Wu, XP (reprint author), Univ Sci & Technol China, Hefei, Anhui, Peoples R China.
期刊名称：INTERNATIONAL JOURNAL OF SATELLITE COMMUNICATIONS AND NETWORKING影响因子和分区
年：2019
卷：37
期：3
页码：283-291
ISSN：1542-0973
关键词：classification; feature extraction; probabilistic neural networks; specific emitter identification
摘要：Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identi ...More
Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(+/- 1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military. ...Hide

DOI：10.1002/sat.1286
百度学术：Specific emitter identification for satellite communication using probabilistic neural networks
语言：外文
被引频次：1
基金：China Postdoctoral Science FoundationChina Postdoctoral Science Foundation [2017M612089]; Fundamental Research Funds for the Central Universities of ChinaFundamental Research Funds for the Central Universities [WK2100060023]
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