Title :
Adaptive array beam forming using a combined RLS-LMS algorithm
Author :
Srar, Jalal Abdulsayed ; Chung, Kah-Seng
Author_Institution :
Dept. of Electr. & Comput. Eng., Curtin Univ. of Technol., Perth, WA
Abstract :
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.
Keywords :
AWGN; adaptive signal processing; array signal processing; convergence; matrix algebra; mean square error methods; recursive estimation; adaptive array beam forming; additive white Gaussian noise; combined RLS-LMS algorithm; convergence performance; correlation matrix; mean square error methods; recursive least square-least mean square algorithm; signal-to-noise ratio; Adaptive algorithm; Adaptive arrays; Additive white noise; Algorithm design and analysis; Computer simulation; Convergence; Least squares approximation; Least squares methods; Mean square error methods; Resonance light scattering; LMS algorithm; RLMS algorithm; RLS algorithm; adaptive array beam forming; array processing;
Conference_Titel :
Communications, 2008. APCC 2008. 14th Asia-Pacific Conference on
Conference_Location :
Tokyo
Print_ISBN :
978-4-88552-232-1
Electronic_ISBN :
978-4-88552-231-4