Performance Improvement in Alternate Mainbeam Nulling by Adaptive Estimation of Convergence Parameters in Linearly Constrained Adaptive Arrays

  • Published : 2009.09.30

Abstract

A novel approach is presented to improve the array performance of the alternate mainbeam nulling in a linearly constrained adaptive array processor in coherent environment. The convergence parameters in the linearly constrained LMS algorithm with a unit gain constraint and a null constraint in the direction of the desired signal are adaptively estimated to reduce the error power between the desired signal and the array output in the 2-dimensional convergence parameter space. It is shown that the case for estimating the convergence parameter for the unit gain constraint with that for null constraint fixed performs best. Also, it is observed that the proposed method performs significantly better than conventional methods as the number of coherent interferences increases.

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References

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