Fast Stable STAP Algorithms Based on Feedback Orthogonalization

The aim of this paper is to present a new fast-convergent numerically stable space-time adaptive processing (STAP) algorithm derived using a novel technique of feedback orthogonalization. The main advantages of this approach lie in its perfected stability to computational errors and faults which makes its real-time implementation on substantially faster and cheaper regular fixed-point processors possible.

[1]  Keshab K. Parhi,et al.  Finite-precision error analysis of QRD-RLS and STAR-RLS adaptive filters , 1997, IEEE Trans. Signal Process..

[2]  B. Parlett The Symmetric Eigenvalue Problem , 1981 .

[3]  Alexander M. Haimovich,et al.  An eigenanalysis interference canceler , 1991, IEEE Trans. Signal Process..

[4]  I. Reed,et al.  Rapid Convergence Rate in Adaptive Arrays , 1974, IEEE Transactions on Aerospace and Electronic Systems.

[5]  G. Bienvenu,et al.  Optimality of high resolution array processing using the eigensystem approach , 1983 .

[6]  K. Gerlach,et al.  Convergence Properties of Gram-Schmidt and SMI Adaptive Algorithms , .

[7]  Karl Gerlach,et al.  Convergence properties of Gram-Schmidt and SMI adaptive algorithms. II , 1990 .

[8]  John M. Cioffi,et al.  Limited-precision effects in adaptive filtering , 1987 .

[9]  Arthur Albert,et al.  Regression and the Moore-Penrose Pseudoinverse , 2012 .

[10]  Zhiyun Ren,et al.  Numerical characteristics of fast recursive least squares transversal adaptation algorithms - A comparative study , 1992, Signal Process..

[11]  Andrzej Cichocki,et al.  Adaptive Blind Signal and Image Processing - Learning Algorithms and Applications , 2002 .

[12]  M. Melamed Detection , 2021, SETI: Astronomy as a Contact Sport.

[13]  H. V. Trees Detection, Estimation, And Modulation Theory , 2001 .

[14]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[15]  Magnus R. Hestenes,et al.  Conjugate Direction Methods in Optimization , 1980 .