A new direction-of-arrival estimation method exploiting signal structure information

作者: Bo Lin , Jiying Liu , Meihua Xie , Jubo Zhu , Fengxia Yan

DOI: 10.1007/S11045-015-0339-2

关键词:

摘要: A new method is proposed to estimate the direction-of-arrival (DOA) based on uniform linear array sampling and named as sparsity temporal correlation exploiting (SaTC-E). By structure information of source signals, including spatial sources, SaTC-E accomplishes DOA estimation with superior performance via block sparse bayesian learning methodology grid refined strategy. applicable into time-varying manifold scenario, such wideband array, provided that matrix determinable. It has improved some other merits, resolution, requirement for a few snapshots, no knowledge number, applicability spatially temporally corrected sources. Real data tests numerical simulations are carried out demonstrate advantages SaTC-E.

参考文章(25)
Michael E Tipping, Sparse bayesian learning and the relevance vector machine Journal of Machine Learning Research. ,vol. 1, pp. 211- 244 ,(2001) , 10.1162/15324430152748236
Jong Min Kim, Ok Kyun Lee, Jong Chul Ye, Compressive MUSIC: Revisiting the Link Between Compressive Sensing and Array Signal Processing IEEE Transactions on Information Theory. ,vol. 58, pp. 278- 301 ,(2012) , 10.1109/TIT.2011.2171529
Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao, Compressed Sensing of EEG for Wireless Telemonitoring With Low Energy Consumption and Inexpensive Hardware IEEE Transactions on Biomedical Engineering. ,vol. 60, pp. 221- 224 ,(2013) , 10.1109/TBME.2012.2217959
Zhang-Meng Liu, Zhi-Tao Huang, Yi-Yu Zhou, An Efficient Maximum Likelihood Method for Direction-of-Arrival Estimation via Sparse Bayesian Learning IEEE Transactions on Wireless Communications. ,vol. 11, pp. 1- 11 ,(2012) , 10.1109/TWC.2012.090312.111912
M M Hyder, K Mahata, Direction-of-Arrival Estimation Using a Mixed $\ell _{2,0}$ Norm Approximation IEEE Transactions on Signal Processing. ,vol. 58, pp. 4646- 4655 ,(2010) , 10.1109/TSP.2010.2050477
Xinpeng Du, Lizhi Cheng, Three stochastic measurement schemes for direction-of-arrival estimation using compressed sensing method Multidimensional Systems and Signal Processing. ,vol. 25, pp. 621- 636 ,(2014) , 10.1007/S11045-012-0220-5
Zhilin Zhang, Bhaskar D. Rao, Extension of SBL Algorithms for the Recovery of Block Sparse Signals With Intra-Block Correlation IEEE Transactions on Signal Processing. ,vol. 61, pp. 2009- 2015 ,(2013) , 10.1109/TSP.2013.2241055
Wei Zhu, Bai-Xiao Chen, Novel methods of DOA estimation based on compressed sensing Multidimensional Systems and Signal Processing. ,vol. 26, pp. 113- 123 ,(2015) , 10.1007/S11045-013-0239-2
E. Tom Northardt, Igal Bilik, Yuri I. Abramovich, Spatial Compressive Sensing for Direction-of-Arrival Estimation With Bias Mitigation Via Expected Likelihood IEEE Transactions on Signal Processing. ,vol. 61, pp. 1183- 1195 ,(2013) , 10.1109/TSP.2012.2232654
Jing Wan, Zhilin Zhang, Jingwen Yan, Taiyong Li, B. D. Rao, Shiaofen Fang, Sungeun Kim, S. L. Risacher, A. J. Saykin, Li Shen, Sparse Bayesian multi-task learning for predicting cognitive outcomes from neuroimaging measures in Alzheimer's disease computer vision and pattern recognition. pp. 940- 947 ,(2012) , 10.1109/CVPR.2012.6247769