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作 者:余瑞浩 严颂华[1,2] YU Rui-hao;YAN Song-hua(School of Electronic Information,Wuhan University,Wuhan 430072,China;Institute of Aerospace Science and Technology,Wuhan University,Wuhan 430072,China)
机构地区:[1]武汉大学电子信息学院,武汉430072 [2]武汉大学宇航科学与技术研究院,武汉430072
出 处:《科学技术与工程》2020年第3期1145-1151,共7页Science Technology and Engineering
基 金:国家自然科学基金(41571420)。
摘 要:利用导航卫星作为信号源进行双基地合成孔径成像是一种新的遥感成像手段。利用导航卫星成像的关键是成像分辨率,而双基地点扩散函数(point spread function,PSF)和多星点扩散函数(multi-satellite point spread function,MPSF)在成像拓扑结构设计和分析成像分辨率上有重要意义,但是目前缺乏对导航卫星成像的多星点扩散函数研究。针对此问题,首先研究利用北斗中圆地球轨道(medium earth orbit,MEO)/倾斜地球同步轨道(inclined geosynchironous orbit,IGSO)卫星和地面静止接收机形成的成像拓扑结构的双基地点扩散函数模型;其次,通过对具有不同方向角的双基地点扩散函数进行非相干累加得到了多星点扩散函数的数学模型,并对分辨率参数进行了分析,然后通过现场实验验证了点扩散函数计算的正确性;最后,针对多星成像中存在伪像的问题,提出基于多星点扩散函数的目标分离算法。结果表明:使用目标分离算法能够对正确地分离出多星成像中的伪像。Bistatic synthetic aperture imaging using navigation satellites as signal source is a new remote sensing method.Imaging resolution is a crucial challenge in this process.In addition,Bistatic point spread function(PSF)and multi-satellite point spread function(MPSF)play import role in the design of imaging topology and analysis of imaging resolution.Recently problems exist in studying MPSF about imaging based on navigation satellites.To solve this problem,firstly,the model of PSF based on imaging topology structure,i.e.using Beidou medium earth orbit(MEO)/inclined geosynchronous orbit(IGSO)satellites as transmitter and employing a ground stationary receiver for receiving,is explored.Then,the mathematical model of MPSF is obtained by incoherent accumulation of bistatic PSF from different orientation angles.Meanwhile,the resolution parameters are analyzed and the validity of PSF calculation is verified by field experiments.Finally,a target separation algorithm based on MPSF is proposed to overcome the problem of artifacts in multi-satellite imaging.The simulation and experimental results show that the target separation algorithm can correctly separate the artifacts in multi-satellite imaging.
关 键 词:合成孔径成像 MEO/IGSO 双基地点扩散函数 多星点扩散函数 目标分离
分 类 号:TP751.1[自动化与计算机技术—检测技术与自动化装置]
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