TENCON 2009 - 2009 IEEE Region 10 Conference 2009
DOI: 10.1109/tencon.2009.5396256
|View full text |Cite
|
Sign up to set email alerts
|

Adaptive RLMS algorithm for antenna array beamforming

Abstract: This paper presents a flexible method of achieving either fixed or self-adaptive antenna beamforming. It involves the use of an array image factor ' d A , which interfaces an RLS and LMS sections in cascade to form the RLMS beamforming algorithm. It is shown that an accurate fixed beam can be obtained by prior setting the elements of ' d A with prescribed values for the required direction. Moreover, the beam direction can also be made adaptive to automatically track the target signal. In this case, a convenien… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
7
0
5

Year Published

2010
2010
2022
2022

Publication Types

Select...
5
2
1

Relationship

1
7

Authors

Journals

citations
Cited by 15 publications
(12 citation statements)
references
References 7 publications
0
7
0
5
Order By: Relevance
“…Unbiased impulse response-based least mean square algorithm is presented in [13]. Performance of RLS and LMS is analyzed and a new method which combines both the algorithms is called RLS adaptive beamformer has been devised in [14][15][16]. RLS algorithm has better convergence rate as compared to LMS algorithm, but its computational complexity for multiple input multiple output (MIMO) is large.…”
Section: Normalized Lms (Nlms) Algorithmmentioning
confidence: 99%
“…Unbiased impulse response-based least mean square algorithm is presented in [13]. Performance of RLS and LMS is analyzed and a new method which combines both the algorithms is called RLS adaptive beamformer has been devised in [14][15][16]. RLS algorithm has better convergence rate as compared to LMS algorithm, but its computational complexity for multiple input multiple output (MIMO) is large.…”
Section: Normalized Lms (Nlms) Algorithmmentioning
confidence: 99%
“…O rastreamento do sinal depende exclusivamente do algoritmo de conformação de feixe. Dentre eles, pode-se destacar os algoritmos da classe LMS e RLS, e inclusive a combinação RLMS (Srar, 2009). Nos últimos anos, vários pesquisadores (Bershad, 2008), (Candido, 2008), têm investigado como melhorar a convergência do LMS, RLS e suas variantes afim de reduzir a complexidade com base no filtro adaptativo.…”
Section: Introductionunclassified
“…Motivado pelo esquema de gradiente estocástico − (Cândido et al, 2010) e pelo resultado apresentado em (Srar et al, 2009), destaca-se o uso da combinação afim nos algoritmos clássicos RLS e LMS para um maior número de elementos no arranjo de antenas e variação da relação sinal ruído mais interferência.…”
Section: Introductionunclassified
“…Se prueba su capacidad de filtrado para diferentes arreglos de antenas y su habilidad de generar el lóbulo de radiación principal hacia el Ángulo de Arribo Deseado (AAD). Finalmente, el análisis del costo computacional determina la cantidad de recursos utilizados en su proceso de cálculo frente a otros esquemas en cascada (Srar y Chung, 2009;Orozco et al, 2013) que utilizan filtros MCP y RMC. A continuación se detalla la organización del artículo.…”
Section: Introductionunclassified