A Robust Method of Emitter Signal Deinterleaving Approach Based on Point Cloud Detection

Yifei Liu, Mingliang Tao, Shuting Tang, Jian Xie, Ling Wang

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Radar signal deinterleaving is a critical prerequisite process for electromagnetic situational awareness. Traditional deinterleaving approaches fail to deal with the emitter with advanced complex pulse repetition interval (PRI). In this paper, a robust deinterleaving method based on point cloud detection is proposed to estimate PRI and extract pulse sequences under complex PRI modulations. It converts pulse sequences to 2-D scatter plots which present straight lines on some specific planes by plane transformation technique. Then utilize the point cloud detection method of Random Sample Consensus (RANSAC) to extract the points on these lines corresponding to specific emitters. It can enhance the semantic features of the pulse train and reduce the sensitivity to algorithm parameters and modulation type. Experimental results demonstrate the effectiveness of the proposed method.

源语言英语
主期刊名2023 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9789463968096
DOI
出版状态已出版 - 2023
活动35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023 - Sapporo, 日本
期限: 19 8月 202326 8月 2023

出版系列

姓名2023 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023

会议

会议35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023
国家/地区日本
Sapporo
时期19/08/2326/08/23

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