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Paper data
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Title:
Achieving superresolution by subspace eigenanalysis in multidimensional spaces

Author(s):
Radoi Emanuel, Military Technical Academy
Quinquis Andre, ENSIETA
Totir Felix, Military Technical Academy

Page numbers in the proceedings:
Volume I pp 205-208

Session:
Parameter Estimation and Statistical Signal Analysis

Paper abstract
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An extension of superresolution methods MUSIC (MUltiple SIgnal Classification) and ESPRIT (Estimation of Signal Parameters by Rotational Invariance Techniques) to spaces of arbitrary dimension is proposed in the paper. Generalizations of signal model, spatial smoothing method and estimate equations are provided. Although many applications can be considered in the areas of radar and wireless communications, only one of them is considered for simulation results: high resolution 3D radar target imaging. The concluding remarks drawn in the final part of the paper are supported by simulation results performed on echo signals from a synthetic target. The discussed methods are also compared to the scattering center extraction using the Fourier transform.

Paper
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A PDF version is available here

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