收稿：2018-01-11，
录用：2018-5-23，
纸质出版：2019-03
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面向微纳卫星高分辨率对地遥感，将超分辨率成像应用于中国整星60公斤级的CX-6(02)微纳卫星设计中，解决因体积和重量限制导致传统长焦距、大口径成像载荷无法应用于微纳卫星的问题。图像获取上，采用高帧频面阵CMOS探测器对同一地物目标多次曝光的方式，利用卫星姿态控制偏差和地速补偿来获得多帧具有亚像元位移的图像；超分辨率重建算法上，在变分贝叶斯框架下提出加权双向差分模型，提高先验概率模型的方向约束性，削弱观测方程求解的病态性。CX-6(02)星成像数据实验结果表明，本文的图像采样方法可获得较为充分的亚像元信息；相比传统的L1范数先验和全变分先验的变分贝叶斯超分辨算法重建结果，本文重建结果对反卷积运算导致的噪声放大具有更好的抑制作用，可获得两倍分辨率提升，有效提高数据质量和应用价值。
Micro-nano satellite is one of the developing trends of remote sensing technology with the advantages of light-weight
small size
low cost. However
because of the limitation of the volume and weight
the traditional high resolution optical imaging payload with long focal length and large aperture is difficult to apply to earth observation of micro-nano satellite. In order to solve this problem
a super-resolution imaging scheme is demonstrated in this paper. First
in the mode of images acquisition
to obtain multi frame images of the same region
the velocity of imaging relative to the ground should be controlled by satellite attitude. And because the attitude control deviation of satellite is objective
so subpixel displacement information can be generated by pitching
yaw
and rolling random deviations
without to install any other displacement generators; Secondly
In the super-resolution reconstruction algorithm
aiming at solving the problem of prior constraints on variational bayesian super-resolution reconstruction method
we propose a weighted bi-directional difference prior model to overcome the under-constraint of non-edge regions of image due to total variation prior and L1 norm prior
to further restrain the solving space of the observation equation. The above scheme is applied to the China’s first super-resolution imaging micro-nano satellite:CX-6(02) micro-nano satellite. The imaging results of this satellite show that: our images acquisition method can obtain sufficient subpixel information
which is approximately uniformly distributed with 0.1 pixel magnitude; The result of super-resolution reconstruction is superior to the same variational bayesian method based on L1 norm prior model and total variation prior model
it is hardly to introduce or amplify the computational noise in the iterative process of the algorithm
effectively weakens the ill-posed property of the deconvolution operation. Make the CX-6(02) satellite’s imaging resolution increased from 2.8 to 1.4 meters in the 700 km orbit altitude
and the whole satellite is only 66 kg. Except for micro-nano satellite
the design scheme of this paper can also be applied to medium or large optical imaging satellite
it may provide a certain theoretical and experimental support for high resolution earth-observing remote sensing.
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