Journal ArticleDOI
The constrained conjugate gradient algorithm
TLDR
The new constrained conjugate gradient (CCG) algorithm is derived from the condition for equivalence between linearly constrained minimum-variance filters and their generalized sidelobe canceler (GSC) implementations.Abstract:
Based on the condition for equivalence between linearly constrained minimum-variance (LCMV) filters and their generalized sidelobe canceler (GSC) implementations, we derive the new constrained conjugate gradient (CCG) algorithm. We discuss the use of orthogonal and nonorthogonal blocking matrices for the GSC structure and how the choice of this matrix may affect the relationship with the LCMV counterpart. The newly derived algorithm was tested in a computer experiment for adaptive multiuser detection and showed excellent results.read more
Citations
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Journal ArticleDOI
Reduced-Rank STAP Schemes for Airborne Radar Based on Switched Joint Interpolation, Decimation and Filtering Algorithm
TL;DR: The simulation results show that the proposed RR-SJIDF STAP schemes with both the RLS and the CCG algorithms converge at a very fast speed and provide a considerable SINR improvement over the state-of-the-art reduced-rank schemes.
Journal ArticleDOI
Constrained adaptive filtering algorithms based on conjugate gradient techniques for beamforming
Lei Wang,R.C. de Lamare +1 more
TL;DR: This article proposes constrained adaptive algorithms based on the conjugate gradient (CG) method for adaptive beamforming according to the minimum variance and constant modulus criteria subject to a constraint on the array response.
Journal ArticleDOI
DOA estimation under unknown mutual coupling and multipath
TL;DR: A new method for direction of arrival (DOA) estimation in the presence of multipath propagation and mutual coupling for a frequency hopping (FH) system is proposed and a maximum likelihood estimator is derived for both the mutual coupling matrix and DOA estimation.
Journal ArticleDOI
On the equivalence of RLS implementations of LCMV and GSC processors
TL;DR: It is proved that the two adaptive implementations of the constrained recursive least squares algorithm are equivalent everywhere regardless of the blocking matrix chosen, which guarantees that algorithm tuning is not affected by theblocking matrix.
Book ChapterDOI
Constrained Adaptive Filters
TL;DR: In the next pages the reader will find an introduction to optimal constrained filters, some of the most widely used adaptation algorithms, alternatives to the direct-form structure for implementation, and a newly proposed structure based on Householder transformations.
References
More filters
Book
Adaptive Filter Theory
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.
Journal ArticleDOI
An algorithm for linearly constrained adaptive array processing
TL;DR: A constrained least mean-squares algorithm has been derived which is capable of adjusting an array of sensors in real time to respond to a signal coming from a desired direction while discriminating against noises coming from other directions.
Journal ArticleDOI
An alternative approach to linearly constrained adaptive beamforming
L.J. Griffiths,C. Jim +1 more
TL;DR: A beamforming structure is presented which can be used to implement a wide variety of linearly constrained adaptive array processors and is shown to incorporate algorithms which have been suggested previously for use in adaptive beamforming as well as to include new approaches.
Journal ArticleDOI
Analysis of conjugate gradient algorithms for adaptive filtering
Pi Sheng Chang,Alan N. Willson +1 more
TL;DR: Two approaches to the implementation of the conjugate gradient algorithm for filtering where several modifications to the original CG method are proposed are presented and it is shown that in finite word-length computation and close to steady state, the algorithms' behaviors are similar to the steepest descent algorithm.