Direction of arrival estimation based on smooth support vector regression
Xiang He, Bin Jiang, Zhong Jingli, Sun Yueguang, Zemin Liu · 2010
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.