Radar signal recognition method based on SVM model

Letian Tian; Zhaowen Zeng; Zhiyang Chang; Sheng Zhang

doi:10.1117/12.2661773

28 December 2022 Radar signal recognition method based on SVM model

Letian Tian, Zhaowen Zeng, Zhiyang Chang, Sheng Zhang

Author Affiliations +

Proceedings Volume 12506, Third International Conference on Computer Science and Communication Technology (ICCSCT 2022); 125062K (2022) https://doi.org/10.1117/12.2661773
Event: International Conference on Computer Science and Communication Technology (ICCSCT 2022), 2022, Beijing, China

Abstract

Radar signal recognition is a key step of electronic reconnaissance. In order to use various parameters of radar signal to identify its country in complex electromagnetic environment, this paper analyses the characteristics of radar signal and the development status of related recognition methods. Aiming at the support vector machine (SVM) classification algorithm in machine learning, this paper studies the feature selection and the establishment, evaluation and optimization of model, and completes the programming and application of the algorithm, the recognition accuracy and efficiency are improved. The research shows that when SVM is applied to radar signal recognition, the classification accuracy is more than 93% and the AUC value is more than 0.99.

Citation Download Citation

Letian Tian, Zhaowen Zeng, Zhiyang Chang, and Sheng Zhang "Radar signal recognition method based on SVM model", Proc. SPIE 12506, Third International Conference on Computer Science and Communication Technology (ICCSCT 2022), 125062K (28 December 2022); https://doi.org/10.1117/12.2661773

Access the abstract

PROCEEDINGS
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data modeling

Radar

Performance modeling

Feature selection

Optimization (mathematics)

Statistical modeling

Statistical analysis

Show All Keywords

RELATED CONTENT

Exploring multitask learning for steganalysis
Proceedings of SPIE (March 22 2013)

Penalized logistic regressions predict stock price trends
Proceedings of SPIE (August 23 2022)

Daily stress detection by using electrocardiogram in the first hour...
Proceedings of SPIE (June 08 2023)

Auto insurance fraud detection based on Logistic-SVM algorithm
Proceedings of SPIE (May 04 2022)

Statistical assessment of model fit for SAR sea clutter
Proceedings of SPIE (October 30 2009)

Statistical assessment of model fit for synthetic aperture radar data
Proceedings of SPIE (August 27 2001)

Second-order interacting multiple model algorithm for tracking maneuvering targets
Proceedings of SPIE (October 22 1993)

Subscribe to Digital Library

Receive Erratum Email Alert

Show All Keywords

Keywords/Phrases

Search In:

Publication Years