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Kalman filter for adaptive antennas

Kalman filter for adaptive antennas Adaptive control algorithm is a key technique for an adaptive array. It is necessary to find a fast and efficient algorithm for gaining rapid interference suppression. Convergence speed of conventional gradient-based algorithms is extremely slow and very sensitive to eigenvalue spread of autocorrelation matrix. This paper presents the Kalman filtering method to adaptive array processing. It has good transient response and achieves faster convergence speed, so it is most suitable for complicated adaptive systems. We analyzed its convergence performance which proved to be related to initial value for P (0). Computer simulation by applying four elements array to null steering was carried out. It is shown that fast convergence needs only 2 M numbers of iteration. The less the value was selected for P (0), the slower convergence was found. Further, if P (0) were too small, the method would not be able to converge. On the other hand, bigger values of P (0) can not achieve more improvement in convergence performance. Simulation also discovered steady response denoted with SNIR dependent on the power of reference signal. These results demonstrate the validity and effectiveness of the Kalman type adaptive antenna. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wuhan University Journal of Natural Sciences Springer Journals

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References (3)

Publisher
Springer Journals
Copyright
Copyright © 1998 by Springer
Subject
Mathematics; Mathematics, general; Computer Science, general; Physics, general; Life Sciences, general
ISSN
1007-1202
eISSN
1993-4998
DOI
10.1007/BF02827549
Publisher site
See Article on Publisher Site

Abstract

Adaptive control algorithm is a key technique for an adaptive array. It is necessary to find a fast and efficient algorithm for gaining rapid interference suppression. Convergence speed of conventional gradient-based algorithms is extremely slow and very sensitive to eigenvalue spread of autocorrelation matrix. This paper presents the Kalman filtering method to adaptive array processing. It has good transient response and achieves faster convergence speed, so it is most suitable for complicated adaptive systems. We analyzed its convergence performance which proved to be related to initial value for P (0). Computer simulation by applying four elements array to null steering was carried out. It is shown that fast convergence needs only 2 M numbers of iteration. The less the value was selected for P (0), the slower convergence was found. Further, if P (0) were too small, the method would not be able to converge. On the other hand, bigger values of P (0) can not achieve more improvement in convergence performance. Simulation also discovered steady response denoted with SNIR dependent on the power of reference signal. These results demonstrate the validity and effectiveness of the Kalman type adaptive antenna.

Journal

Wuhan University Journal of Natural SciencesSpringer Journals

Published: Jun 1, 1998

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