Space Precession Target Classification Based on Radar High-Resolution Range Profiles
Joint Authors
Wang, Yizhe
Feng, Cunqian
Zhang, Yongshun
He, Sisan
Source
International Journal of Antennas and Propagation
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-02-27
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Precession is a common micromotion form of space targets, introducing additional micro-Doppler (m-D) modulation into the radar echo.
Effective classification of space targets is of great significance for further micromotion parameter extraction and identification.
Feature extraction is a key step during the classification process, largely influencing the final classification performance.
This paper presents two methods for classifying different types of space precession targets from the HRRPs.
We first establish the precession model of space targets and analyze the scattering characteristics and then compute electromagnetic data of the cone target, cone-cylinder target, and cone-cylinder-flare target.
Experimental results demonstrate that the support vector machine (SVM) using histograms of oriented gradient (HOG) features achieves a good result, whereas the deep convolutional neural network (DCNN) obtains a higher classification accuracy.
DCNN combines the feature extractor and the classifier itself to automatically mine the high-level signatures of HRRPs through a training process.
Besides, the efficiency of the two classification processes are compared using the same dataset.
American Psychological Association (APA)
Wang, Yizhe& Feng, Cunqian& Zhang, Yongshun& He, Sisan. 2019. Space Precession Target Classification Based on Radar High-Resolution Range Profiles. International Journal of Antennas and Propagation،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1158086
Modern Language Association (MLA)
Wang, Yizhe…[et al.]. Space Precession Target Classification Based on Radar High-Resolution Range Profiles. International Journal of Antennas and Propagation No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1158086
American Medical Association (AMA)
Wang, Yizhe& Feng, Cunqian& Zhang, Yongshun& He, Sisan. Space Precession Target Classification Based on Radar High-Resolution Range Profiles. International Journal of Antennas and Propagation. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1158086
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1158086