@inproceedings{ec319a0f25d74d6187bd3472ee8a40c1,
title = "Specific Emitter Identification Through Demodulation Embedding in Convolutional Neural Networks Using Raw Real Signals",
abstract = "This paper introduces a Specific Emitter Identification (SEI) methodology with a Demodulation Embedding Convolutional Neural Network (DE-CNN). Distinct from prior research endeavors, the paper focuses on analyzing raw real signals, bypassing the traditional down-conversion and I/Q demodulation process to retain more of the intrinsic characteristics of the transmitted signal. Our approach embedding an I/Q demodulation layer within the CNN, enabling efficient preprocessing of raw real signals for SEI. Based on the analog impairment function of SMW200A signal generator, we obtained a transmit signal with analog I/Q imbalance in the semi-physical simulation. Compared with the original I/Q signal,the method based on the raw real signals can improve by up to 3.4 percent.",
keywords = "CNN, I/Q imbalance, SEI, analog impairment, real signals",
author = "Hongbo Li and Jian Zhao and Yaqin Zhao and Longwen Wu",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 ; Conference date: 07-07-2024 Through 12-07-2024",
year = "2024",
doi = "10.1109/IGARSS53475.2024.10642058",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS) ",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "10422--10425",
booktitle = "IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Proceedings",
address = "美国",
}