Title :
A fast algorithm for the two-dimensional covariance method of linear prediction
Author :
Marple, S. Lawrence, Jr.
Author_Institution :
Acuson Corp, Mountain View, CA, USA
Abstract :
This paper presents a new fast computational algorithm for the solution of the least squares normal equations of the two-dimensional (2-D) covariance method of linear prediction. The fast algorithm exploits the near-to-doubly-Toeplitz structure of the normal equations when expressed in matrix form. This algorithm is useful for generating high resolution imagery from coherent imaging system in-phase/quadrature (I/Q) data, such as synthetic aperture radar (SAR)
Keywords :
Toeplitz matrices; covariance analysis; image resolution; least squares approximations; prediction theory; radar imaging; synthetic aperture radar; 2D covariance method; I/Q data; SAR; Toeplitz matrix; coherent imaging system; fast computational algorithm; high resolution imagery; in-phase/quadrature data; least squares normal equations; linear prediction; near-to-doubly-Toeplitz structure; synthetic aperture radar; two-dimensional covariance method; Ear; Equations; High-resolution imaging; Image generation; Image resolution; Least squares methods; Nonlinear filters; Spatial resolution; Two dimensional displays; Vectors;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479931
