Paper data
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
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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