Kalman filter for adaptive antennas |
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Authors: | Hu Jiayuan Zhong Haibin |
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Institution: | (1) College of Electronic Information, Wuhan University, 430072 Wuhan, China |
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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 forP(0). Computer simulation by applying four elements array to null steering was carried out. It is shown that fast convergence
needs only 2M numbers of iteration. The less the value was selected forP(0), the slower convergence was found. Further, ifP(0) were too small, the method would not be able to converge. On the other hand, bigger values ofP(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.
Supported by the Natural Science Foundation of Hubei Province
Hu Jiayuan: born in 1941, Associate professor |
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Keywords: | kalman filter adaptive antenna convergence speed |
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