Correlation based Imaging for rotating satellites
Matan Leibovich, George Papanicolaou, and Chrysoula Tsogka

TL;DR
This paper introduces a correlation-based imaging method for fast-moving, rotating satellites that improves resolution by using a rank-1 eigenvector approach, accounting for Doppler and rotational effects.
Contribution
It proposes a novel two-point migration imaging technique that enhances resolution for rotating satellites by leveraging cross-correlation data and eigenvector analysis.
Findings
Rank-1 imaging outperforms single-point migration in resolution.
Rotation induces diffraction-limited resolution improvements.
Theoretical analysis confirms the benefits of the two-point interference matrix.
Abstract
We consider imaging of fast moving small objects in space, such as low earth orbit satellites, which are also rotating around a fixed axis. The imaging system consists of ground based, asynchronous sources of radiation and several passive receivers above the dense atmosphere. We use the cross-correlation of the received signals to reduce distortions from ambient medium fluctuations. Imaging with correlations also has the advantage of not requiring any knowledge about the probing pulse and depends weakly on the emitter positions. We account for the target's orbital velocity by introducing the necessary Doppler compensation. To image a fast rotating object we also need to compensate for the rotation. We show that the rotation parameters can be extracted directly from the auto-correlation of the data before the formation of the image. We then investigate and analyze an imaging method that…
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