{"title":"High importance feature selection and DV-OSR-QSED strategy for open-set recognition","authors":"Tong Xu","doi":"10.1049/ell2.70167","DOIUrl":null,"url":null,"abstract":"<p>A significant challenge in the domain of anti-drone warfare is the identification of enemies or own aircraft through the analysis of data broadcast by drones (e.g. ADS-B). This issue can be conceptualized as an open set recognition (OSR) problem. This paper proposes a DV-OSR-QSED framework for the purpose of data visualization-based OSR (DV-OSR). Phase-based 2D high-importance features are extracted, the DV-OSR framework is designed and mapped to 2D, and the 5th and 95th quantile selection-Euclidean distance (QSED) strategy is proposed. Experiments show that by using the proposed framework, the correct classification rate for known and unknown samples is 96.04% and 95.79%, the recall rate and <i>F</i>1 value are 89.00% and 92.27%, and the AUC is 0.9630.</p>","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70167","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronics Letters","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/ell2.70167","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
A significant challenge in the domain of anti-drone warfare is the identification of enemies or own aircraft through the analysis of data broadcast by drones (e.g. ADS-B). This issue can be conceptualized as an open set recognition (OSR) problem. This paper proposes a DV-OSR-QSED framework for the purpose of data visualization-based OSR (DV-OSR). Phase-based 2D high-importance features are extracted, the DV-OSR framework is designed and mapped to 2D, and the 5th and 95th quantile selection-Euclidean distance (QSED) strategy is proposed. Experiments show that by using the proposed framework, the correct classification rate for known and unknown samples is 96.04% and 95.79%, the recall rate and F1 value are 89.00% and 92.27%, and the AUC is 0.9630.
期刊介绍：
Electronics Letters is an internationally renowned peer-reviewed rapid-communication journal that publishes short original research papers every two weeks. Its broad and interdisciplinary scope covers the latest developments in all electronic engineering related fields including communication, biomedical, optical and device technologies. Electronics Letters also provides further insight into some of the latest developments through special features and interviews.
Scope
As a journal at the forefront of its field, Electronics Letters publishes papers covering all themes of electronic and electrical engineering. The major themes of the journal are listed below.
Antennas and Propagation
Biomedical and Bioinspired Technologies, Signal Processing and Applications
Control Engineering
Electromagnetism: Theory, Materials and Devices
Electronic Circuits and Systems
Image, Video and Vision Processing and Applications
Information, Computing and Communications
Instrumentation and Measurement
Microwave Technology
Optical Communications
Photonics and Opto-Electronics
Power Electronics, Energy and Sustainability
Radar, Sonar and Navigation
Semiconductor Technology
Signal Processing
MIMO
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