Underdetermined Wideband DOA Estimation Based on Distributed Compressive Sensing

Ying JIANG; Bingqie WANG; Jun HAN; Yi HE

doi:10.11999/JEIT180723

Volume 41 Issue 7

Jul. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(7): 1690-1697

Ying JIANG, Bingqie WANG, Jun HAN, Yi HE. Underdetermined Wideband DOA Estimation Based on Distributed Compressive Sensing[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1690-1697. doi: 10.11999/JEIT180723

Citation:

Ying JIANG, Bingqie WANG, Jun HAN, Yi HE. Underdetermined Wideband DOA Estimation Based on Distributed Compressive Sensing[J]. Journal of Electronics & Information Technology, 2019, 41(7): 1690-1697. doi: 10.11999/JEIT180723

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Underdetermined Wideband DOA Estimation Based on Distributed Compressive Sensing

doi: 10.11999/JEIT180723 cstr: 32379.14.JEIT180723

Ying JIANG¹,
Bingqie WANG¹,
Jun HAN¹,
Yi HE^{2
,
,}

1.
Air Force Early Warning Academy, Wuhan 430000, China
2.
Naval Research Academy, Beijing 100161, China

Funds: The National Natural Science Foundation of China(61771484), The Natural Science Foundation of Hubei Province (2016CFB288)

Received Date: 2018-07-18
Rev Recd Date: 2019-01-11

Available Online: 2019-01-22

Publish Date: 2019-07-01

Abstract

Abstract

In order to realize underdetermined wideband Direction Of Arrival(DOA) estimation based on sparse array, an algorithm on account of Distributed Compressive Sensing(DCS) is proposed. Firstly, wideband signal processing model based on sparse array is deduced and the underdetermined wideband DOA estimation is formulated as a DCS problem. Then, the DCS-Simultaneous Orthogonal Matching Pursuit(DCS-SOMP) algorithm is utilized to solve this problem. Finally, the off-grid problem is considered and a joint DCS model containing off-grid parameters is established. Estimations of DOAs and off-grid parameters are achieved through iterative solution. Simulation results show that the proposed algorithm is effective and have advantages in resolution and computational complexity.
- Direction Of Arrival(DOA) estimation,
- Distributed Compressive Sensing(DCS),
- Sparse array,
- Joint sparsity,
- Off-grid problem

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References(19)

References

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