基于MLBF的毫米波双站SAR前视Omega-k成像算法
投稿时间:2016-08-02  修订日期:2016-10-24  点此下载全文
引用本文:马超,张小虎,杨建超,顾红,苏卫民.基于MLBF的毫米波双站SAR前视Omega-k成像算法[J].红外与毫米波学报,2017,36(4):490~497].MA Chao,ZHANG Xiao-Hu,YANG Jian-Chao,GU Hong,SU Wei-Min.Omega-k algorithm based on MLBF for millimeter wave bistatic forward-looking SAR imaging[J].J.Infrared Millim.Waves,2017,36(4):490~497.]
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作者单位E-mail
马超 南京理工大学 nust_macao@126.com 
张小虎 南京理工大学 zhangxiaohucn@163.com 
杨建超 南京理工大学 yangjianchao999@126.com 
顾红 南京理工大学 nust_guhong@126.com 
苏卫民 南京理工大学 nust_suweimin@126.com 
基金项目:江苏省自然科学基金(批准号:BK20160847);国家自然科学基金(批准号:61471198)
中文摘要:前视成像有着很大的潜在应用价值,比如飞机的导航、导弹寻的打击以及军事侦查等。毫米波合成孔径雷达(SAR)有着分辨率高、体积小、重量轻以及合成孔径时间短等优点。论文结合毫米波体制和双站SAR前视成像技术,开展毫米波双站SAR前视成像算法的研究。在双站SAR前视成像系统中,较大的前视角引入了多普勒质心偏移和严重的距离徙动,因此普通双站SAR的成像算法无法直接移植到双站SAR前视成像中。针对以上问题,论文首先提出了一种基于瞬时多普勒分析的改进Loffeld's Bistatic Formula (MLBF)二维频谱求解方法,相比于现有方法,该方法能更准确的得到双站SAR前视回波信号的二维频谱。在此基础上又推导出了适用于毫米波双站SAR前视成像的Omega-k算法;最后通过仿真实验,验证了提出算法的有效性和优越性。
中文关键词:双站合成孔径雷达  前视成像  MLBF  Omega-k算法
 
Omega-k algorithm based on MLBF for millimeter wave bistatic forward-looking SAR imaging
Abstract:Bistatic forward-looking synthetic aperture radar (BFSAR) has many potential applications, such as self-landing in bad weather, military detection. Millimeter-wave SAR has high resolution, light weight small size and short synthetic aperture time advantages. Therefore, this paper combines millimeter-wave and BFSAR techniques, carry out the research of imaging algorithms for millimeter-wave BFSAR. However, imaging algorithms for BFSAR are the difficulties of the study. Due to the special forward-looking geometry, imaging algorithms for bistatic SAR can not be applied to BFSAR directly. So, this paper proposes a modified Loffeld's Bistatic Formula (MLBF). The new method compared with other extended Loffeld's Bistatic Formula (ELBF) can obtain a bistatic point target reference spectrum, which is accurate enough for bistatic forward-looking configuration. Then, an Omega-k algorithm based on the reference spectrum is derived. Finally, simulations validate the accuracy of the MLBF method and the effectiveness of the Omega-k imaging algorithm.
keywords:Bistatic SAR  Forward-looking imaging  MLBF  Omega-k algorithm
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