One-Dimensional Multi-Frame Blind Deconvolution Using Astronomical Data for Spatially Separable Objects
Technical Report,01 Sep 2018,26 Mar 2020
AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH WRIGHT-PATTERSON AFB United States
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Blind deconvolution is used to complete missions to detect adversary assets in space and to defend the nations assets. A new algorithm was developed to perform blind deconvolution for objects that are spatially separable using multiple frames of data. This new one-dimensional approach uses the expectation-maximization algorithm to blindly deconvolve spatially separable objects. This object separation reduces the size of the object matrix from an NxN matrix to two singular vectors of length N. With limited knowledge of the object and point spread function the one-dimensional algorithm successfully deconvolved the objects in both simulated and laboratory data.
- Unmanned Spacecraft