Specific Emitter Identification Based on Variational Mode Decomposition and Spectral Features in Single Hop and Relaying Scenarios

计算机科学 共发射极 希尔伯特-黄变换 模式识别(心理学) 特征提取 人工智能 稳健性(进化) 熵(时间箭头) 信号处理 算法 语音识别 电子工程 物理 电信 白噪声 工程类 基因 量子力学 生物化学 化学 雷达
作者
Udit Satija,Nikita Trivedi,Gagarin Biswal,Barathram Ramkumar
出处
期刊:IEEE Transactions on Information Forensics and Security [Institute of Electrical and Electronics Engineers]
卷期号:14 (3): 581-591 被引量:152
标识
DOI:10.1109/tifs.2018.2855665
摘要

Specific emitter identification is the process of identifying or discriminating different emitters based on the radio frequency fingerprints extracted from the received signal. Due to inherent non-linearities of the power amplifiers of emitters, these fingerprints provide distinguish features for emitter identification. In this paper, we develop an emitter identification based on variational mode decomposition and spectral features (VMD-SF). As VMD decomposes the received signal simultaneously into various temporal and spectral modes, we choose to explore different spectral features, including spectral flatness, spectral brightness, and spectral roll-off for improving the identification accuracy contrary to existing temporal features-based methods. For demonstrating the robustness of VMD in decomposing the received signal into emitter-specific modes, we also develop a VMD-entropy and moments (EM 2 ) method based on existing temporal features extracted from the Hilbert Huang transform of the emitter-specific temporal modes. Our proposed method has three major steps: received signal decomposition using VMD, feature extraction, and emitter identification. We evaluate the performance of the proposed methods using the probability of correct classification (F cc ) both in single hop and in relaying scenario by varying the number of emitters. To demonstrate the superior performance of our proposed methods, we compared our methods with the existing empirical mode decomposition-(entropy-, first-, and second-order moments) (EMD-EM 2 ) method both in terms of F cc and computational complexity. Results depict that the proposed VMD-SF emitter identification method outperforms the proposed VMD-EM 2 method and the existing EMD-EM 2 method both in single hop and relaying scenarios for a varying number of emitters. In addition, the proposed VMD-SF method has lowest computational cost as compared with the aforementioned methods.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
HHH发布了新的文献求助10
1秒前
1秒前
1秒前
香爆脆发布了新的文献求助10
2秒前
bsn完成签到 ,获得积分10
3秒前
落寞依珊应助跳跃的洪纲采纳,获得20
4秒前
激情的三毒完成签到,获得积分10
4秒前
LF完成签到,获得积分10
4秒前
4秒前
123发布了新的文献求助10
5秒前
mark发布了新的文献求助10
6秒前
Hello应助葡萄采纳,获得30
7秒前
雨过天晴发布了新的文献求助10
7秒前
顾矜应助LZY采纳,获得10
8秒前
夜雨完成签到,获得积分10
9秒前
9秒前
Cuisine完成签到 ,获得积分10
10秒前
10秒前
高兴的小完成签到,获得积分10
11秒前
还单身的寒云完成签到,获得积分10
11秒前
11秒前
Waris完成签到 ,获得积分10
12秒前
12秒前
陶陶完成签到,获得积分10
12秒前
曹庆威完成签到,获得积分10
13秒前
wbing完成签到,获得积分10
14秒前
14秒前
雪山飞龙发布了新的文献求助10
14秒前
15秒前
王老吉发布了新的文献求助10
15秒前
16秒前
hsp关闭了hsp文献求助
17秒前
山东老铁发布了新的文献求助10
17秒前
yiyi131发布了新的文献求助10
17秒前
17秒前
17秒前
19秒前
FashionBoy应助卢健辉采纳,获得10
19秒前
sujiaoziemo完成签到,获得积分10
20秒前
有只猫叫一区给有只猫叫一区的求助进行了留言
20秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Indomethacinのヒトにおける経皮吸収 400
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 370
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
Aktuelle Entwicklungen in der linguistischen Forschung 300
Current Perspectives on Generative SLA - Processing, Influence, and Interfaces 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3992659
求助须知:如何正确求助?哪些是违规求助? 3533545
关于积分的说明 11262911
捐赠科研通 3273209
什么是DOI,文献DOI怎么找? 1805969
邀请新用户注册赠送积分活动 882889
科研通“疑难数据库(出版商)”最低求助积分说明 809545