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Article Dans Une Revue IEEE Internet of Things Journal Année : 2020

Design of a Robust Radio-Frequency Fingerprint Identification Scheme for Multimode LFM Radar

Yuexiu Xing
Aiqun Hu
Junqing Zhang
Jiabao Yu
Guyue Li
Ting Wang

Résumé

Radar is an indispensable part of the Internet of Things (IoT). Specific emitter identification is essential to identify the legitimate radars and, more importantly, to reject the malicious radars. Conventional methods rely on pulse parameters that are not capable to identify the specific emitter as two radars may have the same configuration or a malicious radar can perform spoofing attacks. Radio frequency fingerprint (RFF) is the unique and intrinsic hardware characteristic of devices resulted from hardware imperfection, which can be used as the device identity. This paper proposes a robust and reliable radar identification scheme based on the RFF, taking linear frequency modulation (LFM) radar as a case study. This scheme first classifies the operation mode of the pulses, then eliminates the noise effect, and finally identifies the radar emitters based on the transient and modulation-based RFF features. Experimental results verify the effectiveness of our radar identification scheme among three real LFM radars (same model) operating at four modes, each mode with 2,000 pulses from each radar. The identification rates of the four modes are all higher than 90% when the signal-tonoise ratio (SNR) is about 5 dB. In addition, mode 3 achieves almost 100% identification accuracy even when the SNR is as low as-10 dB.
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Dates et versions

hal-04317473 , version 1 (05-12-2023)

Identifiants

  • HAL Id : hal-04317473 , version 1

Citer

Yuexiu Xing, Aiqun Hu, Junqing Zhang, Jiabao Yu, Guyue Li, et al.. Design of a Robust Radio-Frequency Fingerprint Identification Scheme for Multimode LFM Radar. IEEE Internet of Things Journal, 2020, 7, pp.10581 - 10593. ⟨hal-04317473⟩
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