基于物理约束迭代反卷积算法的空间目标识别

Signal Recovery and Synthesis Pub Date : 1900-01-01 DOI:10.1364/srs.1998.stub.2

J. Christou, E. Hege, S. Jefferies, M. Cheselka

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引用次数: 1

摘要

将一种物理约束迭代反褶积算法应用于自适应光学系统获得的模拟和实际人造卫星(空间物体)观测数据。讨论了获取良好的点扩展函数信息的相关问题，所采用的算法不仅可以重建目标，还可以重建相应的点扩展函数。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Space Object Identification using a Physically Constrained Iterative Deconvolution Algorithm

A physically constrained iterative deconvolution algorithm is applied to both simulated and real artificial satellite (space object) observations obtained with adaptive optical systems. The problems associated with obtaining good point spread function information is discussed and the algorithm applied also permits reconstruction of not only the object but also the corresponding point spread functions.

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Signal Recovery and Synthesis

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