Decorrelation Algorithm Based on Singular Value Decomposition

JI Zhengyan; CHEN Hui; ZHANG Jiajia; LI Shuai; LU Xiaofei

doi:10.11999/JEIT161157

Volume 39 Issue 8

Aug. 2017

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JI Zhengyan, CHEN Hui, ZHANG Jiajia, LI Shuai, LU Xiaofei. Decorrelation Algorithm Based on Singular Value Decomposition[J]. Journal of Electronics & Information Technology, 2017, 39(8): 1913-1918. doi: 10.11999/JEIT161157

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JI Zhengyan, CHEN Hui, ZHANG Jiajia, LI Shuai, LU Xiaofei. Decorrelation Algorithm Based on Singular Value Decomposition[J]. Journal of Electronics & Information Technology, 2017, 39(8): 1913-1918. doi: 10.11999/JEIT161157

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Decorrelation Algorithm Based on Singular Value Decomposition

doi: 10.11999/JEIT161157

Received Date: 2016-10-28
Rev Recd Date: 2017-04-21
Publish Date: 2017-08-19

Abstract

Abstract

To solve the problem of coherent sources using sparse reconstruction method, this paper proposes an improved method for solving coherent sources using the eigenvectors corresponding to the largest eigenvalues after Singular Value Decomposition (SVD) decomposition of received data. The method reconstructs the angle by iterating the feature vector, and reconstructs the angle information accurately without knowing the number of the signal source. Compared with the classical SVD algorithm, the operation speed is faster, and the sparse reconstruction effect is better. Theoretical analysis and simulation results verify the good performance of the algorithm.
- Signal processing,
- Sparse reconstruction,
- Decoherence,
- Singular Value Decomposition (SVD)

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References(18)

References

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