Multi-polarized HRRP classification by SVM ensemble

Authors:
Xiaodan Wang;Chunying Zheng;Xu Yao;Lei Lei
Affiliations:
Department of Computer Engineering, Air Force Engineering University, China;Department of Computer Engineering, Air Force Engineering University, China;Department of Computer Engineering, Air Force Engineering University, China;Department of Computer Engineering, Air Force Engineering University, China
Venue:
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Year:
2011

Citing 3
Cited 0

Combining Pattern Classifiers: Methods and Algorithms

Combining Pattern Classifiers: Methods and Algorithms
Pattern Recognition and Machine Learning (Information Science and Statistics)

Pattern Recognition and Machine Learning (Information Science and Statistics)
Radar HRRP target recognition based on higher order spectra

IEEE Transactions on Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

A high range resolution profile (HRRP) is a good characteristic for radar target, and radar target recognition by using HRRP has been studied extensively. Target recognition by fusion the target features of multiple polarimetric directions is studied in this paper, the framework of multi-polarized HRRP classification by SVM ensemble is given, and a novel approach of multi-polarized range profile classification by SVM dynamic ensemble based on fuzzy integral is proposed. Experiments on the measured multi-polarized HRRP indicate the effectiveness of our conclusion.