A Support Vector Machine MUSIC Algorithm
IEEE Transactions on Antennas and Propagation(2012)
摘要
This paper introduces a new Support Vector Machine (SVM) formulation for the direction of arrival (DOA) estimation problem. We establish a theoretical relationship between the Minimum Variance Distortionless Response (MVDR) and the MUltiple SIgnal Characterization (MUSIC) methods. This leads naturally to the derivation of an SVM-MUSIC algorithm, which combines the benefits of subspace methods with those of SVM. Spatially smoothed versions and a recursive form of the algorithms exhibit good performance against coherent signals. We test the method's performance in scenarios with noncoherent and coherent signals, and in small-sample size-situations obtaining an improved performance in comparison with existing standard approaches.
更多查看译文
关键词
Support vector machines,Multiple signal classification,Arrays,Estimation,Direction of arrival estimation,Standards,Noise
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络