A Novel Method for Abrupt Motion Change Radar Target Detection Based on Generalized Radon-Fourier Transform

Siyuan Liu, Zegang DIng, Xu Zhou, Pengjie You

科研成果: 书/报告/会议事项章节会议稿件同行评审

3 引用 (Scopus)

摘要

Long-time integration is an effective method to improve the signal-to-noise ratio (SNR) and detection performance of highly maneuvering targets. The existing methods for long-time integration mainly focus on detecting targets with high-order motion under fixed model, losing sight of the possibility that targets may have an abrupt motion change at an unknown instant. Therefore, this paper proposes a novel long-time integration method for highly maneuvering target with abrupt change model (ACM) based on generalized Radon-Fourier transform (GRFT), which could coherently integrate the target echoes before and after ACM and obtain the optimal coherent integration gain. The simulation and experiment results show that the proposed method can detect the ACM target under the condition of extremely low SNR and improve the detection performance compared with the fixed model GRFT.

源语言英语
主期刊名ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9781728123455
DOI
出版状态已出版 - 12月 2019
活动2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019 - Chongqing, 中国
期限: 11 12月 201913 12月 2019

出版系列

姓名ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019

会议

会议2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019
国家/地区中国
Chongqing
时期11/12/1913/12/19

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