Title :
Direction of arrival estimation based on smooth support vector regression
Author :
Xiang, He ; Bin, Jiang ; Jingli, Zhong ; Yueguang, Sun ; Liu, Zemin
Author_Institution :
Commun. Commanding Acad., Wuhan, China
Abstract :
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.
Keywords :
antenna arrays; antenna theory; array signal processing; direction-of-arrival estimation; regression analysis; support vector machines; vectors; DOA; MUSIC; all-direction peak value searching technique; direction of arrival estimation; smooth support vector regression; support vector machines; Constraint optimization; Convergence; Direction of arrival estimation; Helium; Machine learning; Multiple signal classification; Neural networks; Smoothing methods; Sun; Support vector machines; Direction of Arrival(DOA) estimation; Support Vector Machine(SVM); smooth support vector regression(SSVR);
Conference_Titel :
Future Computer and Communication (ICFCC), 2010 2nd International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5821-9
DOI :
10.1109/ICFCC.2010.5497314