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Motion parameter estimation of high‐speed manoeuvering targets based on hybrid integration and synchrosqueezing transform
Author(s) -
Lin Hua,
Zeng Chao,
Zhang Hai,
Jiang Ge
Publication year - 2022
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/rsn2.12225
Subject(s) - computer science , estimation , motion (physics) , algorithm , artificial intelligence , engineering , systems engineering
In this study, we address the problem of estimating the motion parameters of multiple high‐speed manoeuvering targets under low signal‐to‐noise ratio (SNR) environment with a low‐range resolution radar, where the target movement could cause the echo signal energy seriously spread across both the range and Doppler frequency coordinates, and the returned signals from different targets would merge into each other. Based on the subaperture feature enhancement, Hough transform (HT) and the second‐order short‐time Fourier‐based synchrosqueezing transform (FSST2), a novel method, named as EHFSST2, is proposed. The proposed method can robustly extract the targets of interest from environment and accurately estimate the targets' motion parameters. Thanks to its ability to compensate the effects of the range walk, curvature, and the Doppler ambiguity, spreading, wrapping, and the energy of echo signal can be coherently integrated along the target's individual moving trajectory. In addition, several numerical experiments are provided to demonstrate the effectiveness. The results show that the proposed method is superior to some existing methods in terms of the anti‐noise ability, measurement accuracy and integration performance.

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