標題: Maximum likelihood DOA estimation based on the cross-entropy method
作者: Chen, Yen-Chih
Su, Yu T.
電信工程研究所
Institute of Communications Engineering
公開日期: 2006
摘要: In this paper, we propose two simulation based maximum likelihood (ML) methods to estimate the direction of arrival (DOA) by a novel combination of the Cross-Entropy (CE) method and the polynomial parameterization scheme. The CE method is an efficient stochastic approximation method for solving both discrete and continuous optimization problems. We bridge the ML approach and the stochastic search algorithm by properly randomizing the desired parameters. Numerical results show that the proposed CE-based algorithms yield highly accurate DOA estimation with fast convergence rate while requiring only linear processing complexity. Compared with the conventional iterative quadratic maximization likelihood (IQML) method, the proposed algorithms can alleviate the error propagation effect in low signal to noise ratio (SNR) region and asymptotically approach the Cramer-Rao bound in high SNR region.
URI: http://hdl.handle.net/11536/17487
http://dx.doi.org/10.1109/ISIT.2006.261734
ISBN: 978-1-4244-0505-3
DOI: 10.1109/ISIT.2006.261734
期刊: 2006 IEEE International Symposium on Information Theory, Vols 1-6, Proceedings
起始頁: 851
結束頁: 855
Appears in Collections:Conferences Paper


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