A Fast Sparse Decomposition for Three-order Polynomial Phase Signal Based on Subspace

OU Guojian; JIANG Qingping; QING Changchun

doi:10.11999/JEIT170593

Volume 40 Issue 3

Mar. 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(3): 648-655

OU Guojian, JIANG Qingping, QING Changchun. A Fast Sparse Decomposition for Three-order Polynomial Phase Signal Based on Subspace[J]. Journal of Electronics & Information Technology, 2018, 40(3): 648-655. doi: 10.11999/JEIT170593

Citation:

OU Guojian, JIANG Qingping, QING Changchun. A Fast Sparse Decomposition for Three-order Polynomial Phase Signal Based on Subspace[J]. Journal of Electronics & Information Technology, 2018, 40(3): 648-655. doi: 10.11999/JEIT170593

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A Fast Sparse Decomposition for Three-order Polynomial Phase Signal Based on Subspace

doi: 10.11999/JEIT170593 cstr: 32379.14.JEIT170593

1.
2.
(Key Laboratory of Aerocraft Tracking Telemetering &
3.
(School of Software, Chongqing College of Electronic Engineering, Chongqing 401331, China)

Funds:

The project of ChongQing municipal education Commission (KJ1602909, KJ1503004), The National Natural Science Foundation of China (61371164), Intelligent Robot Techndogy Research Center of Electronic Engineering (XJPT201705)

Received Date: 2017-06-21
Rev Recd Date: 2017-11-29
Publish Date: 2018-03-19

Abstract

Abstract

In view of the defect for large number of atoms in the over-complete dictionary during sparse decomposition, this paper presents a fast sparse decomposition algorithm for three-order polynomial phase signal based on subspace. According to the characteristic of three-order polynomial phase signal, the original signal is transformed into two subspace signals, then the atoms are structured based on the two subspace signals in the over-complete dictionary, and the two subspace signals are sparsely decomposed by using orthogonal matching pursuit algorithm. Finally, the sparse decomposition for the original signal is completed by using the theory of the sparse decomposition. In the algorithm, three-order polynomial phase signal is transformed into two subspace signals, and two over-complete dictionaries are structured based on the two subspace signals. Compared to one over-complete dictionary, the atoms are reduced enormously by using two over-complete dictionaries in the algorithm, and one matching atom can be obtained in one over-complete dictionary when another matching atom in another over-complete dictionary is obtained by using fast Fourier transform. Therefore the method can sparsely decompose three-order polynomial phase signal with low computational complexity by reducing the atoms and using fast Fourier transform. Simulation results show that the computational efficiency of the proposed method is better than that of using Gabor atoms, genetic algorithm and the algorithm based on modulation correlation partition, and the sparsity is better.
- Three-order Polynomial Phase Signal (PPS),
- Subspace,
- Fast Fourier Transform (FFT),
- Orthogonal Matching Pursuit (OMP),
- Sparse decomposition

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References(33)

References

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