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2022
Conference Paper
Title
RSO feature extraction using Super ResolutionWavelets and Inverse Radon Transform
Abstract
In this paper an algorithm to extract the geometrical and motion parameters of Resident Space Objects (RSO) in lower earth orbit (LEO) with a sophisticated simulation environment is proposed. The performance of super resolution wavelets for time frequency analysis of the radar echos in lower SNR conditions is illustrated. The rotation rate of the RSO is estimated using 2D autocorrelation of the joint time frequency spectrum. The maximum size of the object on the image projection plane and Doppler frequency is estimated by concentrating the point scatterers using inverse Radon transform.
Author(s)