Direction of Arrival Estimation Based on Minor Component Analysis Approach

  • Donghai Li
  • Shihai Gao
  • Feng Wang
  • Fankun Meng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4233)


Many high resolution DOA estimation algorithms like MUSIC and ESPRIT estimation are based on the sub-space concept and require the eigen-decomposition of the input correlation matrix. As quantities of computation of eigen-decomposition, it is unsuitable for real time processing. An algorithm for noise subspace estimation based on minor component analysis is proposed. These algorithms are based on anti-Hebbian learning neural network and contain only relatively simple operations, which are stable, convergent, and have self-organizing properties. Finally a method of real-time parallel processing is proposed, and data processing can be finished at end time of sampling. Simulations show that the proposed algorithm has an analogy performance with the MUSIC algorithm.


Analogy Performance Signal Subspace Noise Subspace Music Algorithm Arrival Estimation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Donghai Li
    • 1
  • Shihai Gao
    • 1
  • Feng Wang
    • 1
  • Fankun Meng
    • 1
  1. 1.Zhengzhou Information Science and Technology InstituteZhengzhouChina

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