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Superresolution techniques based on the Multiple Signal Classification (MUSIC) have recently been applied to two-dimensional (2-D) Inverse Synthetic Aperature Radar (ISAR) imaging with demonstrated results. These techniques exhibit a much higher spatial resolution than other approaches using a 2-D Fourier transform. This paper presents a MUSIC-based superresolution algorithm for three-dimensional (3-D) radar imaging, which is especially useful for measurements with both small frequency and aspect angle (in azimuth and elevation) spans. This algorithm models the measured 3-D data set as a sum of point source emisisons plus noise. Once the positions in the 3-D space of such scattering centres are obtained by using the MUSIC algorithm, the weights (or RCS) of the scattering centres are obtained through a pseudo-inverse matrix inversion computed by means of a Singular Value Decomposition (SVD).

Additional information

Authors: BAQUERO M, JRC Ispra (IT);FORTUNY J, JRC Ispra (IT);NESTI G, JRC Ispra (IT);SIEBER A J, JRC Ispra (IT)
Bibliographic Reference: Paper presented: 17th Meeting and Symposium AMTA, Williamsburg (US), November 13-17, 1995
Availability: Available from (1) as Paper EN 39469 ORA
Record Number: 199610101 / Last updated on: 1996-02-16
Original language: en
Available languages: en