An ISAR autofocus imaging algorithm based on FCN and transfer learing

Lianzi WANG; Ling WANG; Daiyin ZHU

doi:10.7527/S1000-6893.2023.28172

ACTA AERONAUTICAET ASTRONAUTICA SINICA >

2023 , Vol. 44 >Issue 17: 328172 - 328172

DOI: https://doi.org/10.7527/S1000-6893.2023.28172

Electronics and Electrical Engineering and Control

An ISAR autofocus imaging algorithm based on FCN and transfer learing

Lianzi WANG ,
Ling WANG ,
Daiyin ZHU

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College of Electronic and information Engineering，Nanjing University of Aeronautics and Astronautics，Nanjing 210016，China

E-mail： tulip_wling@nuaa.edu.cn

Received date: 2022-10-26

Revised date: 2022-11-17

Accepted date: 2023-01-11

Online published: 2023-02-10

Supported by

National Natural Science Foundation of China(61871217);Aeronautical Science Foundation of China(20182052011);Shanghai Aerospace Science and Technology Innovation Fund(SAST2021-026);Fund of Prospective Layout of Scientific Research for NUAA （Nanjing University of Aeronautics and Astronautics）(ILA220581A22)

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Abstract

The targets of Inverse Synthetic Aperture Radar （ISAR） imaging are mostly non-cooperative， and motion compensation is the key of ISAR imaging when the relative motion status of target is unknown. Fully Convolutional Network （FCN） has excellent feature extraction and fitting abilities， and an ISAR phase compensation algorithm based on FCN and Transfer Learning is proposed by utilizing the FCN in ISAR autofocusing in this paper. Firstly， a large number of simulation data sets with different phase errors are constructed and trained to provide phase compensation ability for FCN. In addition， the transfer training of simulation and measured data with different attitudes is carried out to improve the translational phase compensation ability. The measured data processing results show that the performance of FCN phase compensation algorithm is better than traditional algorithm， which verifies the effectiveness in the proposed method and the superiority compared with the traditional method.

Key words： inverse synthetic aperture radar; imaging; phase compensation; fully convolutional neural network; transfer learning

Cite this article

Lianzi WANG , Ling WANG , Daiyin ZHU . An ISAR autofocus imaging algorithm based on FCN and transfer learing[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023 , 44(17) : 328172 -328172 . DOI: 10.7527/S1000-6893.2023.28172

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