Title :
Iterative MMSE method and recurrent Kalman procedure for ISAR image reconstruction
Author_Institution :
Military Acad. for Artillery & Air Defence
fDate :
10/1/2001 12:00:00 AM
Abstract :
This work presents a novel approximate iterative and recurrent approach for image reconstruction from inverse synthetic aperture radar (ISAR) data. Mathematical models of the quadrature components of the ISAR signal, reflected by an object with a complex geometry, are devised. Approximation matrix functions are used to describe deterministic signals reflected by point scatterers located at nodes of the uniform grid (model) during inverse aperture synthesis. Minimum mean square error (MMSE) equations and Kalman equations are derived. To prove the validity and correctness of the developed iterative MMSE method and recurrent Kalman procedure, numerical experiments were performed. The computational results demonstrate high resolution images, unambiguous and convergent estimates of the point scatterers´ intensities of a target from simulated ISAR data
Keywords :
Kalman filters; image restoration; iterative methods; least mean squares methods; radar computing; radar imaging; radar resolution; synthetic aperture radar; ISAR image reconstruction; approximation matrix functions; correlation algorithms; deterministic signals; high resolution images; image restoration; iterative MMSE method; mathematical models; point scatterers; quadrature components; recurrent Kalman procedure; recurrent approach; unambiguous convergent estimates; uniform grid nodes; vector measurement equation; vector state equation; Equations; Geometry; Image reconstruction; Inverse problems; Inverse synthetic aperture radar; Iterative methods; Kalman filters; Mathematical model; Radar scattering; Signal synthesis;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
