Adaptive array beam forming using a combined RLS-LMS algorithm
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A new adaptive algorithm, called RLMS, which combines the use of recursive least square (RLS) and least mean square (LMS), is proposed for array beam forming. The convergence of the RLMS algorithm is analyzed, in terms of mean square error, in the presence of additive white Gaussian noise. Computer simulation results show that the convergence performance of RLMS is superior to either RLS or LMS operating on its own. Furthermore, the convergence of RLMS is quite insensitive to changes in either signal-to-noise ratio, or the initial value of the input correlation matrix for the RLS section, or the step size adopted for the LMS section.
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Srar, Jalal Abdulsayed; Chung, Kah-Seng; Mansour, Ali (2010)This paper studies the influence of the use of finite wordlength on the operation of the RLMS adaptive beamformingalgorithm. The convergence behavior of RLMS, based on the minimum mean square error (MSE), is analyzed for ...
Srar, J.; Chung, Kah-Seng; Mansour, A. (2010)This paper studies the influence of the use of finite wordlength on the operation of the RLMS adaptive beamforming algorithm. The convergence behavior of RLMS, based on the minimum mean square error (MSE), is analyzed for ...
Srar, Jalal; Chung, Kah-Seng (2008)This paper examines the performance of an adaptive linear array employing the new RLMS algorithm, which consists of a recursive least square (RLS) section followed by a least mean square (LMS) section. The performance ...