The Radar Signal Deinterleaving Method Base on Point Cloud Segmentation Network

CHEN Tao; QIU Baochuan; XIAO Yihan; YANG Boyi

doi:10.11999/JEIT230622

Volume 46 Issue 4

Apr. 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(4): 1391-1398

CHEN Tao, QIU Baochuan, XIAO Yihan, YANG Boyi. The Radar Signal Deinterleaving Method Base on Point Cloud Segmentation Network[J]. Journal of Electronics & Information Technology, 2024, 46(4): 1391-1398. doi: 10.11999/JEIT230622

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CHEN Tao, QIU Baochuan, XIAO Yihan, YANG Boyi. The Radar Signal Deinterleaving Method Base on Point Cloud Segmentation Network[J]. Journal of Electronics & Information Technology, 2024, 46(4): 1391-1398. doi: 10.11999/JEIT230622

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The Radar Signal Deinterleaving Method Base on Point Cloud Segmentation Network

doi: 10.11999/JEIT230622

College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China

Funds: The National Defense Science and Technology Foundation Enhancement Program (2019-JCJQ-ZD-067-00), Shanghai Aerospace Science and Technology Innovation Fund (SAST2022-063)

Received Date: 2023-06-25
Rev Recd Date: 2023-12-21

Available Online: 2023-12-27

Publish Date: 2024-04-24

Abstract

Abstract

To solve the problems of pixel points overlap and low processing efficiency in existing end-to-end radar signal deinterleaving methods based on image segmentation, an end-to-end sorting method using a point cloud segmentation network is proposed in this paper. Firstly, the Pulse Description Words (PWD) of radar pulse stream are mapped to point clouds. Then, the PointNet++ is used to segment each point according to its radiation source. Finally, the points with the same label are clustered to form pulse sets, and the radiation sources within each pulse set are then extracted to form corresponding emitter description words. The simulation results demonstrate that the proposed method can effectively separate unknown radar signals while maintaining reliability and stability, even in scenarios with pulse loss and false pulse interference. Additionally, the implementation efficiency of this method is higher because of the model with lightweight characteristics.
- Electronic reconnaissance,
- Signal deinterleaving,
- End to end,
- Pulse Description Word (PDW),
- Point clouds

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References(16)

References

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