Micro-motion Recognition of Spatial Cone Target Based on ISAR Image Sequences

The accurate micro-motions recognition of spatial cone target is the foundation of the characteristic parameter acquisition. For this reason, a micro-motion recognition method based on the distinguishing characteristics extracted from the Inverse Synthetic Aperture Radar (ISAR) sequences is proposed...

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Bibliographic Details
Main Authors: Changyong Shu, Fengli Xue, Shengjun Zhang, Peiling Huang, Jinzu Ji
Format: Article
Language:English
Published: Departamento de Ciência e Tecnologia Aeroespacial 2016-04-01
Series:Journal of Aerospace Technology and Management
Subjects:
Online Access:http://www.jatm.com.br/ojs/index.php/jatm/article/download/603
Description
Summary:The accurate micro-motions recognition of spatial cone target is the foundation of the characteristic parameter acquisition. For this reason, a micro-motion recognition method based on the distinguishing characteristics extracted from the Inverse Synthetic Aperture Radar (ISAR) sequences is proposed in this paper. The projection trajectory formula of cone node strong scattering source and cone bottom slip-type strong scattering sources, which are located on the spatial cone target, are deduced under three micro-motion types including nutation, precession, and spinning, and the correctness is verified by the electromagnetic simulation. By comparison, differences are found among the projection of the scattering sources with different micro-motions, the coordinate information of the scattering sources in the Inverse Synthetic Aperture Radar sequences is extracted by the CLEAN algorithm, and the spinning is recognized by setting the threshold value of Doppler. The double observation points Interacting Multiple Model Kalman Filter is used to separate the scattering sources projection of the nutation target or precession target, and the cross point number of each scattering source’s projection track is used to classify the nutation or precession. Finally, the electromagnetic simulation data are used to verify the effectiveness of the micro-motion recognition method.
ISSN:1984-9648
2175-9146