A Novel ISAR Imaging Approach for Maneuvering Targets With Satellite-Borne Platform

Autor:	Jinzhi Ren, Jun Wan, Zhijun Yang, Hongqing Liu, Dong Li, Zhanye Chen
Rok vydání:	2022
Předmět:	Parametric Image Computer science Particle swarm optimization Geotechnical Engineering and Engineering Geology law.invention Azimuth Inverse synthetic aperture radar Coherent processing interval law Entropy (information theory) Projection plane Electrical and Electronic Engineering Radar Algorithm
Zdroj:	IEEE Geoscience and Remote Sensing Letters. 19:1-5
ISSN:	1558-0571 1545-598X
DOI:	10.1109/lgrs.2021.3103901
Popis:	Inverse synthetic aperture radar (ISAR) imaging for maneuvering targets has always been a challenging task due to azimuth time-varying Doppler frequency modulation, especially under moving platform condition. In this case, the common assumption that the image projection plane (IPP) of the radar line-of-sight (LOS) direction is constant during coherent processing interval (CPI) is invalid. To address this issue, a novel ISAR imaging approach for maneuvering targets is proposed by exploiting nonstationary IPP in this article. First, considering time-varying LOS direction, the new geometric and signal models are developed, where 2-D spatial-variant phase error is mainly deduced. After that, a parametric image entropy minimum optimization combined with efficient particle swarm optimization (PSO) is used to obtain optimal motion parameters. In doing so, 2-D spatial-variant phase error terms are compensated accurately to produce well-focused ISAR image. Finally, the effectiveness and superiority of the proposed algorithm are verified by the simulation results and electromagnetic scattering data.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c190761aad10a935167204672a755ae8 https://doi.org/10.1109/lgrs.2021.3103901 Zobrazit plný text záznamu