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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2023, Vol. 44 ›› Issue (8): 327254-327254.doi: 10.7527/S1000-6893.2022.27254

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

SAR image registration algorithm based on echo information of overlapping subaperture

Zheng YE1,2(), Daiyin ZHU1,2, Di WU1,2   

  1. 1.College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
    2.Key Laboratory of Radar Imaging and Microwave Photonics,Ministry of Education,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
  • Received:2022-04-07 Revised:2022-04-25 Accepted:2022-07-04 Online:2023-04-25 Published:2022-07-21
  • Contact: Zheng YE E-mail:yz1994@nuaa.edu.cn
  • Supported by:
    Aeronautical Science Foundation of China(20182052013)

Abstract:

Synthetic Aperture Radar (SAR) image registration is the process of finding the geometric transformation relationship between multiple SAR images to calibrate different images to a unified spatial coordinate system. When traditional optical image registration methods, such as Scale-Invariant Feature Transform (SIFT) combined with Random Sample Consensus (RANSAC) algorithm, are used for SAR image registration, the registration performance is greatly affected by the interference of multiplicative speckle noise. In this paper, a SAR image registration algorithm is proposed based on the echo information of overlapping subaperture. In the imaging processing of the complex echo data, using the phase information and the subaperture autofocusing algorithm, highly correlated overlapping subaperture images are obtained. The multiimage registration methods are used to achieve the subaperture image registration within and between imaging apertures, so as to improve the accuracy of SAR image registration. The processing results of the measured data of several different scenes show that the proposed algorithm has more homonymous points, fewer mismatched point pairs, and smaller root mean square error than the SIFT + RANSAC algorithm. Moreover, the proposed algorithm is more robust to speckle noise, and thereby gains the improved registration performance.

Key words: Synthetic Aperture Radar (SAR), image registration, overlapping subaperture, speckle noise, autofocusing

CLC Number: