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Multi-Function Radar Signal Sorting Based on Complex Network

delete2021-01-01
delete27
PRE
AI
K
Kun Chi
J
Jihong Shen
Y
Yan Li
李
李云杰 (Yunjie Li)
王
王胜 (Sheng Wang) *
DOI:10.1109/LSP.2020.3044259delete
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Abstract

Abstract

En 中文
In complex electromagnetic environments, the challenge of signal sorting task for multi-function radars (MFRs) with various work modes has arisen. The previous methods are prone to cause the so-called increasing batch problem, which means that the work modes of one MFR may be sorted into multiple emitters. In this letter, a MFR signal sorting method based on complex network is proposed to tackle the problem mentioned above. The novel method utilizes limited penetrable visibility graph to construct the network from interleaved radar pulse sequences, then employs label propagation algorithm and density peak clustering to detect community structures, thus fulfilling deinterleaving of pulses from several MFRs. Simulation results show that the proposed method is effective to alleviate the increasing batch problem, and is also robust under non-ideal conditions.
Keywords:
Radar
Sorting
Complex networks
Clustering algorithms
Task analysis
Radar detection
Time series analysis
Community detection
complex network
multi-function radar
signal sorting
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Signal Processing Magazine cover
IEEE Signal Processing Magazine
IF:
9.6
Papers:
1.1W
Citations:
1.7W

Organization

H
Harbin Engineering University
Scholars:
1.9W
Papers: 1.3W
Citations: 1.3W
B
beijing institute of technology
Scholars:
5.5W
Papers: 4.0W
Citations: 63
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