Neural Computing and Applications

, Volume 18, Issue 4, pp 381–385 | Cite as

High-resolution DOA estimation based on independent noise component for correlated signal sources

Original Article


In this article, a modified complex-valued FastICA algorithm is utilized to extract the specific feature of the Gaussian noise component from mixtures so that the estimated component is as independent as possible to the other non-Gaussian signal components. Once the noise basis vector is obtained, we can estimate direction of arrival by searching the array manifold for direction vectors, which are as orthogonal as possible to the estimated noise basis vector especially for highly correlated signals with closely spaced direction. Superior resolution capabilities achieved with the proposed method in comparison with the conventional multiple signal classification (MUSIC) method, the spatial smoothing MUSIC method, and the signal subspace scaled MUSIC method are shown by simulation results.


Antenna array Direction of arrival Independent component analysis Permutation ambiguity Correlated signals 



The authors would like to thank the anonymous reviewers for their valuable and constructive comments, which helped to improve the presentation of the article. This research was supported by the National Science Council under grant number NSC 95-2221-E-275-001.


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Copyright information

© Springer-Verlag London Limited 2008

Authors and Affiliations

  1. 1.Department of Automatic Control EngineeringFeng Chia UniversityTaichungTaiwan, ROC
  2. 2.Reinforcement Headquarters, Ministry of National DefenseTaipeiTaiwan, ROC
  3. 3.Department of Information TechnologyLing Tung UniversityTaichungTaiwan, ROC

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