2-D DOA tracking using variational sparse Bayesian learning embedded with Kalman filter

2-D DOA tracking using variational sparse Bayesian learning embedded with Kalman filter

Abstract In this paper, we consider the 2-D direction-of-arrival (DOA) tracking problem. The signals are captured by a uniform spherical array and therefore can be analyzed in the spherical harmonics domain. Exploiting the sparsity of source DOAs in the whole angular region, we propose a novel DOA t...

Full description

Bibliographic Details
Main Authors: Qinghua Huang, Jingbiao Huang, Kai Liu, Yong Fang
Format: Article
Language:English
Published: SpringerOpen 2018-04-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
2-D direction-of-arrival (DOA) tracking
Spherical array
Transition probabilities (TP) model
Variational sparse Bayesian learning (VSBL)
Kalman filter (KF)
Online Access:http://link.springer.com/article/10.1186/s13634-018-0541-0

Internet

http://link.springer.com/article/10.1186/s13634-018-0541-0

Similar Items