NSSC OpenIR  > 微波遥感部
Alternative TitleThree D imensional Target Feature Extraction Using Curvil inearSynthetic Aperture Radar
刘浩; 吴季; 北京8701信箱
Source Publication遥感技术与应用
Keyword曲线合成孔径雷达 三维目标特征提取 relax算法
Other AbstractIn th is paper, the concep t of Curvilinear Synthetic Aperture Radar(CLSAR)is introduced and the returned ch irp signal datamodel for CL SAR is described. Based on th ismodel, the p rincip le of th ree dimensional target reconstruction of CL SAR is analyzed detailedly.The 2D FFT analysis is conducted in the Cross range- Elevation plane of the curvilinear apertures, and the results show that the traditional FFT- based SAR imaging method is no longer practical in the curvilinear apertures situation because of the effect of large side lobe.As the substitution of the FFT- based imaging method, the 3D target feature extraction method using RELAX algorithm based on spectrum estimation is introduced to solve the sidelobe problem.It has already been proved that the RELAX algorithm can be used efficiently to estimate the dom inant scatters'discrete spectrum parameters from the noise and clutter's continuous spectrum if the targets can be divided into several dom inant scatters. Furthermore,the computer simulation of the ideal full aperture and several specific curvilinear apertures are conducted.The simulation results show the validities and advantages of the RELAX2based 3D target feature extraction method for CLSAR.And the results also show that the parabolic aperture is the relative op timal choice among the curvilinear aperturesw e used in the simulation.
Indexed ByCSCD
Funding Project中国科学院空间科学与应用研究中心
Citation statistics
Cited Times:1[CSCD]   [CSCD Record]
Document Type期刊论文
Corresponding Author北京8701信箱
Recommended Citation
GB/T 7714
刘浩,吴季,北京8701信箱. 基于曲线合成孔径雷达的三维目标特征提取[J]. 遥感技术与应用,2004,19(6):493-497.
APA 刘浩,吴季,&北京8701信箱.(2004).基于曲线合成孔径雷达的三维目标特征提取.遥感技术与应用,19(6),493-497.
MLA 刘浩,et al."基于曲线合成孔径雷达的三维目标特征提取".遥感技术与应用 19.6(2004):493-497.
Files in This Item:
File Name/Size DocType Version Access License
2004196493.pdf(326KB) 开放获取CC BY-NC-SAApplication Full Text
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[刘浩]'s Articles
[吴季]'s Articles
[北京8701信箱]'s Articles
Baidu academic
Similar articles in Baidu academic
[刘浩]'s Articles
[吴季]'s Articles
[北京8701信箱]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[刘浩]'s Articles
[吴季]'s Articles
[北京8701信箱]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.