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作 者:杨晓城 杨真乙 阎敬业 武林 蒋明峰 YANG Xiao-cheng;YANG Zhen-yi;YAN Jing-ye;WU Lin;JIANG Ming-feng(School of Information Science and Technology,Zhejiang Sci-Tech University,Hangzhou,Zhejiang 310018,China;National Space Science Center,Chinese Academy of Sciences,Beijing 100190,China)
机构地区:[1]浙江理工大学信息学院,浙江杭州310018 [2]中国科学院国家空间科学中心,北京100190
出 处:《电子学报》2022年第2期339-345,共7页Acta Electronica Sinica
基 金:国家自然科学基金(No.61672466,No.620115300130);浙江省自然科学基金(No.LY18D060009);浙江省自然科学基金-数理医学学会联合基金重点项目(No.LSZ19F010001);浙江省科技厅重点研发项目(No.2020C03060)。
摘 要:成像反演是综合孔径辐射计的一项关键内容.然而,综合孔径辐射计成像反演是病态的反问题.虽然传统的正则化方法能有效克服其病态性,但依然存在较大的重构误差.为了进一步降低重构误差,提出一种基于拉普拉斯算子的综合孔径辐射计成像算法.与传统的单参数正则化不同,该算法通过引入拉普拉斯算子项,对差分亮温构造拉普拉斯混合正则化,并利用多维扩展的广义交叉验证准则选取2个正则化参数.基于L波段的FPIR样机进行了仿真分析,仿真结果表明:与改进的最小范数正则化和带限正则化相比,该算法均方根误差平均降低了30%,峰值信噪比平均提高了3 dB,证明了其有效性.The imaging inversion is a key content of synthetic aperture interferometric radiometers(SAIRs). However, the imaging inversion in SAIRs is an ill-posed inverse problem. Although the traditional regularization methods can effectively overcome the ill-conditioned property, there is still a large reconstruction error. In order to further reduce the reconstruction error, an imaging algorithm of SAIRs based on Laplace operator is proposed. Different from traditional single-parameter regularization, the proposed algorithm constructs the Laplace hybrid regularization for differential brightness temperature by introducing a new term of Laplace operator. Moreover, two regularization parameters are selected by use of multi-dimensional extended generalized cross-validation criterion. The simulation is based on the prototype of full polarization interferometric radiometer(FPIR). The simulation results show that compared with improved minimum norm regularization and band-limited regularization, the root mean square error for the proposed algorithm has reduced by30%, and the peak signal to noise ratio has increased by3dB, proving its effectiveness.
关 键 词:被动微波遥感 综合孔径辐射计 正则化 重构误差 拉普拉斯算子
分 类 号:TP722.6[自动化与计算机技术—检测技术与自动化装置]
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