Exponentially Weighted Distance-Based Detection for Radiometric Identification

Yong Qiang JIA; Lu GAN; Hong Shu LIAO

doi:10.1587/transfun.E100.A.3086

Exponentially Weighted Distance-Based Detection for Radiometric Identification

Yong Qiang JIA, Lu GAN, Hong Shu LIAO

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Summary :

Radio signals show characteristics of minute differences, which result from various idiosyncratic hardware properties between different radio emitters. A robust detector based on exponentially weighted distances is proposed to detect the exact reference instants of the burst communication signals. Based on the exact detection of the reference instant, in which the radio emitter finishes the power-up ramp and enters the first symbol of its preamble, the features of the radio fingerprint can be extracted from the transient signal section and the steady-state signal section for radiometric identification. Experiments on real data sets demonstrate that the proposed method not only has a higher accuracy that outperforms correlation-based detection, but also a better robustness against noise. The comparison results of different detectors for radiometric identification indicate that the proposed detector can improve the classification accuracy of radiometric identification.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.12 pp.3086-3089

Publication Date: 2017/12/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E100.A.3086

Type of Manuscript: LETTER

Category: Measurement Technology

Authors

Yong Qiang JIA
  University of Electronic Science and Technology of China,the Southwest Electronics and Telecommunication Technology Research Institute
Lu GAN
  University of Electronic Science and Technology of China
Hong Shu LIAO
  University of Electronic Science and Technology of China

Keyword

radiometric identification, radio frequency fingerprint, transient detector

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Yong Qiang JIA, Lu GAN, Hong Shu LIAO, "Exponentially Weighted Distance-Based Detection for Radiometric Identification" in IEICE TRANSACTIONS on Fundamentals, vol. E100-A, no. 12, pp. 3086-3089, December 2017, doi: 10.1587/transfun.E100.A.3086.
Abstract: Radio signals show characteristics of minute differences, which result from various idiosyncratic hardware properties between different radio emitters. A robust detector based on exponentially weighted distances is proposed to detect the exact reference instants of the burst communication signals. Based on the exact detection of the reference instant, in which the radio emitter finishes the power-up ramp and enters the first symbol of its preamble, the features of the radio fingerprint can be extracted from the transient signal section and the steady-state signal section for radiometric identification. Experiments on real data sets demonstrate that the proposed method not only has a higher accuracy that outperforms correlation-based detection, but also a better robustness against noise. The comparison results of different detectors for radiometric identification indicate that the proposed detector can improve the classification accuracy of radiometric identification.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.3086/_p

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@ARTICLE{e100-a_12_3086,
author={Yong Qiang JIA, Lu GAN, Hong Shu LIAO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Exponentially Weighted Distance-Based Detection for Radiometric Identification},
year={2017},
volume={E100-A},
number={12},
pages={3086-3089},
abstract={Radio signals show characteristics of minute differences, which result from various idiosyncratic hardware properties between different radio emitters. A robust detector based on exponentially weighted distances is proposed to detect the exact reference instants of the burst communication signals. Based on the exact detection of the reference instant, in which the radio emitter finishes the power-up ramp and enters the first symbol of its preamble, the features of the radio fingerprint can be extracted from the transient signal section and the steady-state signal section for radiometric identification. Experiments on real data sets demonstrate that the proposed method not only has a higher accuracy that outperforms correlation-based detection, but also a better robustness against noise. The comparison results of different detectors for radiometric identification indicate that the proposed detector can improve the classification accuracy of radiometric identification.},
keywords={},
doi={10.1587/transfun.E100.A.3086},
ISSN={1745-1337},
month={December},}

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TY - JOUR
TI - Exponentially Weighted Distance-Based Detection for Radiometric Identification
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 3086
EP - 3089
AU - Yong Qiang JIA
AU - Lu GAN
AU - Hong Shu LIAO
PY - 2017
DO - 10.1587/transfun.E100.A.3086
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2017
AB - Radio signals show characteristics of minute differences, which result from various idiosyncratic hardware properties between different radio emitters. A robust detector based on exponentially weighted distances is proposed to detect the exact reference instants of the burst communication signals. Based on the exact detection of the reference instant, in which the radio emitter finishes the power-up ramp and enters the first symbol of its preamble, the features of the radio fingerprint can be extracted from the transient signal section and the steady-state signal section for radiometric identification. Experiments on real data sets demonstrate that the proposed method not only has a higher accuracy that outperforms correlation-based detection, but also a better robustness against noise. The comparison results of different detectors for radiometric identification indicate that the proposed detector can improve the classification accuracy of radiometric identification.
ER -