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Support Vector Machine for HRRP Recognition based on Bald Eagle Search Optimization

Published: 15 March 2023 Publication History

Abstract

Applying support vector machine (SVM) on high resolution range profile (HRRP) is a topic of widespread concern in the radar automatic target recognition field. The classification performance of SVM largely depends on its kernel and penalty parameters, parameter optimization is a critical component in target recognition algorithm. In this paper, a target recognition method based on SVM and HRRP is proposed, the SVM method is optimized by introducing bald eagle search (BES) algorithm. The new method adopts BES to optimize the kernel parameter and penalty parameter of SVM, effectively solves the defects of slow convergence and low classification accuracy due to the improper selection of SVM classifier parameters. Experimental analysis shows that the BES-SVM could provide a higher recognition accuracy and lower time consumption compared with traditional SVM and GA-SVM, which has good applicability for HRRP based radar target recognition problems.

References

[1]
Zhao Lihong, Song Ying, Zhu Yushi, Zhang Cheng and Zheng Yi, 2009. Face recognition based on multi-class SVM, Chinese Control and Decision Conference, 5871-5873.
[2]
V N Vapnik. 1995. The Nature of Statistical Learning Theory. New York: Springer- Verlag.
[3]
Y S XIAO, L Z HUANG, J H ZHU, 2014. A new radar target recognition method of the maximal margin kernel optimization. Journal of Signal Processing, 30(7), 783-788.
[4]
F. Ning and F. Tao. 2012. Research of Radar Range Profile's Recognition Based on an Improved C-SVM Algorithm. IEEE 12th International Conference on Computer and Information Technology, 801-804.
[5]
C. H. Zheng, G. W. Zheng, L. C. Jiao and A. L. Ding. 2003. Multi-targets for high-resolution range profile of radar based on fuzzy support vector machine. Proceedings Fifth International Conference on Computational Intelligence and Multimedia Applications, 407-412.
[6]
Tsujitani, M., & Tanaka, Y. 2011. Cross-validation, bootstrap, and support vector machines. Advances in Artificial Neural Systems, 302572:1-302572:6.
[7]
Y. R. Nugraha, A. P. Wibawa and I. A. E. Zaeni. 2019. Particle Swarm Optimization – Support Vector Machine (PSO-SVM) Algorithm for Journal Rank Classification, 2019 2nd International Conference of Computer and Informatics Engineering (IC2IE), 69-73.
[8]
W. Chen and H. -m. Yuan, 2014. An improved GA-SVM algorithm 2014 9th IEEE Conference on Industrial Electronics and Applications, 2137-2141.
[9]
Alsattar, H. A., Zaidan, A. A., Zaidan, B. B. 2020. Novel meta-heuristic bald eagle search optimisation algorithm. Artificial Intelligence Review, 53(3), 2237-2264.
[10]
Z. Kang, F. Ren, H. Zhang, X. Lu and Q. Li, 2021. Diagnosis Method of Transformer Winding Fault Based on Bald Eagle Search Optimizing Support Vector Machines,2021 IEEE 4th International Electrical and Energy Conference (CIEEC), 1-5.

Cited By

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  • (2024)Radar sequence HRRP target recognition based on DRSN-LSTM2024 8th International Conference on Control Engineering and Artificial Intelligence10.1145/3640824.3640834(66-72)Online publication date: 8-Mar-2024
  • (2024)Small Sample Target Recognition Based on Radar HRRP and SDAE-WACGANIEEE Access10.1109/ACCESS.2024.335941912(16375-16385)Online publication date: 2024
  • (2024)Bald eagle search algorithm: a comprehensive review with its variants and applicationsSystems Science & Control Engineering10.1080/21642583.2024.238531012:1Online publication date: Aug-2024

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cover image ACM Other conferences
EITCE '22: Proceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering
October 2022
1999 pages
ISBN:9781450397148
DOI:10.1145/3573428
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 March 2023

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Author Tags

  1. bald eagle search (BES)
  2. high-resolution range profile (HRRP)
  3. radar automatic target recognition (RATR)
  4. support vector machine (SVM)

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EITCE 2022

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Overall Acceptance Rate 508 of 972 submissions, 52%

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Cited By

View all
  • (2024)Radar sequence HRRP target recognition based on DRSN-LSTM2024 8th International Conference on Control Engineering and Artificial Intelligence10.1145/3640824.3640834(66-72)Online publication date: 8-Mar-2024
  • (2024)Small Sample Target Recognition Based on Radar HRRP and SDAE-WACGANIEEE Access10.1109/ACCESS.2024.335941912(16375-16385)Online publication date: 2024
  • (2024)Bald eagle search algorithm: a comprehensive review with its variants and applicationsSystems Science & Control Engineering10.1080/21642583.2024.238531012:1Online publication date: Aug-2024

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