On an artificial neural network for inverse scattering problems
In this paper, we consider artificial neural networks for inverse scattering problems. As a
working model, we consider the inverse problem of recovering a scattering object from the …
working model, we consider the inverse problem of recovering a scattering object from the …
Detection of dispersive targets in synthetic aperture radar images with the help of deep learning
SNV Chidara, M Gilman, R Sah… - … on Analysis and …, 2024 - aimsciences.org
Detection of dispersive targets in SAR is obstructed by ambiguity between the scattering
delay and increase of the signal travel time. To overcome this ambiguity, we design image …
delay and increase of the signal travel time. To overcome this ambiguity, we design image …
Divergence measures and detection performance for dispersive targets in SAR
When electromagnetic waves impinge on objects with complex geometries and/or internal
structure, we can observe scattering that is distributed in time rather than instantaneous. To …
structure, we can observe scattering that is distributed in time rather than instantaneous. To …
Deep learning approach to the detection of scattering delay in radar images
In radar imaging, stochastic target models are routinely used to describe distributed
scatterers. In such models, the reflectivity of a target or clutter is a realization of a stochastic …
scatterers. In such models, the reflectivity of a target or clutter is a realization of a stochastic …