Off-grid Sparse Representation Based Localization Method for Near-field Sources

Yi JIN; Changzhi XU; Tao JING; Xiaohuan WU; Jun YAN; Mingyu LI

doi:10.11999/JEIT200784

Volume 43 Issue 11

Nov. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(11): 3105-3110

Yi JIN, Changzhi XU, Tao JING, Xiaohuan WU, Jun YAN, Mingyu LI. Off-grid Sparse Representation Based Localization Method for Near-field Sources[J]. Journal of Electronics & Information Technology, 2021, 43(11): 3105-3110. doi: 10.11999/JEIT200784

Citation:

Yi JIN, Changzhi XU, Tao JING, Xiaohuan WU, Jun YAN, Mingyu LI. Off-grid Sparse Representation Based Localization Method for Near-field Sources[J]. Journal of Electronics & Information Technology, 2021, 43(11): 3105-3110. doi: 10.11999/JEIT200784

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Off-grid Sparse Representation Based Localization Method for Near-field Sources

doi: 10.11999/JEIT200784

1.
China Academy of Space Technology-Xi’an, Xi’an 710100, China
2.
School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
3.
School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China

Funds: The National Key Research and Development Program (2019YFB1803102); The National Natural Science Foundation of China (61801377, 62171068)

Received Date: 2020-09-08
Rev Recd Date: 2021-10-14

Available Online: 2021-10-21

Publish Date: 2021-11-23

Abstract

Abstract

Near-field source localization is a potential research topic in next-generation wireless communications. Most existing methods focus on traditional subspace based methods or on-grid sparse methods. For the problem that the accuracy of subspace class method loss array aperture and sparse representation method is restricted by mesh effect, an off-grid sparse representation localization method is proposed in this paper. First, by obtaining a high-order cumulant matrix, an angle based off-grid signal model is constructed and then the alternatively iterating optimization method is employed to estimate the angles. For range estimation, a range parameter based off-grid signal model is constructed by using the angle estimation values and is solved by alternatively iterating method. Simulation results reveal that the proposed method not only possesses high estimation accuracy, but also can realize auto-pairing of angles and ranges.
- Near-field localization,
- Sparse representation,
- Off-grid signal model,
- Alternative iteration

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References(15)

References

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