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- Title
A novel framework for extracting moment-based fingerprint features in specific emitter identification.
- Authors
Zhao, Yurui; Wang, Xiang; Sun, Liting; Huang, Zhitao
- Abstract
Extensive experiments illustrate that moments and their derivations can act as effective fingerprint features for specific emitter identification. Nevertheless, the lack of mechanistic explanation restricts the moment-based fingerprint features to a trial-based and data-driven technique. To make up for theoretical weakness and enhance generalization ability, we analytically investigate how intentional modulation and unintentional modulation affect moments. A framework for extracting moment-based fingerprint features is proposed through fine-segmenting slices. Fingerprint features are extracted, followed by segmenting signals into a combination of sinewaves and calculating their moments. The proposed framework shows advantages in mechanism interpretability and generalizing ability. Simulations and experiments verified the correctness and effectiveness of the proposed framework.
- Subjects
HUMAN fingerprints; FEATURE extraction
- Publication
EURASIP Journal on Advances in Signal Processing, 2023, Vol 2023, Issue 1, p1
- ISSN
1687-6172
- Publication type
Article
- DOI
10.1186/s13634-023-00978-4