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Date
2026-04-20
Abstract
We consider Inverse Synthetic Aperture Radar (ISAR) imaging for a rotating scatterer. We begin by employing a linearised scattering model for the case of a rotating scatterer with a known centre of rotation, on a horizontal target plane, being imaged by a point-like transceiver. This model is described using a scattering operator, F, which maps the object’s reflectivity function to a scattered wavefield. The image is obtained by backprojecting the scattered field. The resulting image is the output of the combination, F∗F, applied to the reflectivity function that we wish to image/recover. Utilising microlocal analysis, particularly the wavefront relation of F, we examine the nature of fictitious artifacts that may arise in the reconstructed image. This analysis is used to suggest several experimental setups, which we demonstrate numerically, whereby the artifacts can be guaranteed not to interfere with regions selected for imaging.
We also explore the scenario when the centre of rotation is not known and what can be done to form an accurate image in this situation. Following this, we consider scatterers rotating about a known axis being imaged by static linear and planar transceiver arrays, respectively. By using a linear or planar transceiver, we are able to extend the analysis so that the scatterer is no longer constrained to a plane, and we again show how to avoid artifacts. We investigate conditions under which the restriction of F∗F to the scene to be imaged is a pseudodifferential operator. When these conditions are satisfied, no artifacts appear in the reconstructed image. Therefore, this paper provides valuable theoretical insights into the location of artifacts which appear in the imaging of rotating objects and presents a strategy for the design of data acquisition geometries that avoid such artifacts.
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This article has been published in a revised form in Inverse Problems and Imaging, http://dx.doi.org/10.3934/ipi.2026034. This version is free to download for private research and study only. Not for redistribution, re-sale or use in derivative works.
Publisher
American Institute of Mathematical Sciences (AIMS)
Citation
Inverse Problems and Imaging
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Sustainable Development Goals
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Attribution-NonCommercial-ShareAlike 4.0 International