Earticle

초록

영어

Subspace partition is a common method in normal MUSIC algorithm that divides the signal covariance matrix into signal subspace and noise subspace by eigenvalue decomposition. By this method, the effect of environmental noise is curbed. However, when the signal angle interval becomes small and the signal-noise ratio reduces, some certain limitations in multiple signal estimation such as loss and confusion will be presented, which means the normal method of estimation is unable to distinguish those signals we need actually. A modified MUSIC algorithm is proposed in this paper to solve the problem. A modified part in the spatial spectrum called weighting function is introduced. Some weighted operation are given to the steering vectors when the spatial spectrum is formed, making the most of subspaces and there eigenvalues. Some simulations followed are taken to discuss the performace of the modified method. Through the analysis we can see that, under the condition of a small signal angle interval and a low signal-noise ratio, the improved algorithm could achieve satisfactory result for the DOA estimation.

목차

Abstract
 1. Introduction
 2. Research Method
 3. Results and Discussions
 4. Conclusion
 Acknowledgments
 References

키워드

저자

• Changgan Shu [ State Key Laboratory of IPOC, Beijing University of Posts and Telecommunications, Beijing 100876, China ]
• Yumin Liu [ State Key Laboratory of IPOC, Beijing University of Posts and Telecommunications, Beijing 100876, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605