By Topic

Constrained least squares in adaptive, imperfect arrays

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Najm, W.G. ; Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA

Two new constrained deterministic least-squares algorithms are presented which are capable of enabling a narrow-band zero-order generalized sidelobe canceller (SLC), in the presence of array imperfections, to null out jammers while preserving the friendly look-direction signal with minimal a priori knowledge of the signal environment. The algorithms are capable of solving deterministic least-squares optimization problems subject to an equality constraint in an iterative, adaptive manner by imposing a `soft' constraint via the quadratic penalty function optimization method. The first algorithm is based on the matrix inversion lemma while the second is obtained by means of QR-decomposition using new three-dimensional Givens (1958) rotations and implemented with a systolic array architecture. These new constrained algorithms improve system performance when an artificial injection of a receiver noise vector is introduced

Published in:

Antennas and Propagation, IEEE Transactions on  (Volume:38 ,  Issue: 11 )