Earticle

초록

영어

In this paper we propose an improved MUSIC (Multiple Signal Classification) algorithm applicable for direction of arrival (DOA) estimation of coherent signals in the presence of one-dimensional uniform linear array (ULA), which is based on Toeplitz matrix theory and Fourth-order-cumulants (Foc). In the signal model, a new Toeplitz construction method combining SVD (singular value decomposition) with mean calculation is explored to reconstruct the covariance matrix of array output. The DOA estimation problem can be addressed when the covariance matrix is full-rank. Foc theory is used to eliminate the Gaussian noise in the signals, after that the space of the array matrix is changed, which determines the final signal subspace and noise subspace. According to the subspace, we can adopt the conventional MUSIC to estimate the DOAs of coherent signals. Simulation results show that this algorithm provides a significant performance in comparison with other de-correlation algorithms. It has a better resolution under the condition of small angle interval. In addition, a lower root-mean-square error (RMSE) is obtained at low signal-to-noise (SNR) situation.

목차

Abstract
 1. Introduction
 2. Related theory
  2.1. Toeplitz Matrix
  2.2. Fourth Order Cumulants
 3. Signal Model and T-FOC MUSIC
  3.1. Signal Model
  3.2. T-Foc MUSIC Algorithm
 4. Simulation Analysis
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Xin Zhang [ School of Information Science and Technology, Dalian Maritime University ]
• Xiaoming Liu [ School of Information Science and Technology, Dalian Maritime University ]
• Haixia Yu [ City Institute, Dalian University of Technology Dalian ]
• Chang Liu [ School of Information Science and Technology, Dalian Maritime University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605