Direction of arrival estimation based on smooth support vector regression

Autor:	Jiang Bin, He Xiang, Zemin Liu, Zhong Jingli, Sun Yueguang
Rok vydání:	2010
Předmět:	Estimation Covariance matrix business.industry Computation Direction of arrival Pattern recognition Regression analysis Statistics::Computation Support vector machine Peak value Artificial intelligence Estimation methods business Mathematics
Zdroj:	2010 2nd International Conference on Future Computer and Communication.
Popis:	In this paper, we propose a new approach on direction of arrival (DOA) estimation based on smooth support vector regression. The proposed method can achieve higher accurate estimates for DOA while avoiding the all-direction peak value searching technique used in other traditional DOA estimation methods. Meanwhile, this approach reduces the extensive computations required by conventional super resolution algorithms such as MUSIC and is easier to implement in real-time applications. The proposed method map among the outputs of the array and the DOAs by means of a family of support vector machines. Computer simulation results show the effectiveness of the proposed method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a7799c3558e3496e7d16aa5dffa39fd0 https://doi.org/10.1109/icfcc.2010.5497314 Zobrazit plný text záznamu