Systems Engineering and Electronics ›› 2020, Vol. 42 ›› Issue (9): 1945-1952.doi: 10.3969/j.issn.1001-506X.2020.09.09

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Phase error compensation processing of UAV-borne SAR based on MN-MEA algorithm

Yanheng MA1(), Jianqiang HOU1(), Weimin ZHANG2(), Gen LI1()   

  1. 1. Department of Unmanned Aerial Vehicle, Army Engineering University, Shijiazhuang 050003, China
    2. Unit 73676 of the PLA, Jiangyin 214400, China
  • Received:2019-10-21 Online:2020-08-26 Published:2020-08-26
  • Supported by:
    军内科研项目;双重实验室建设项目资助课题

Abstract:

Unmanned aerial vehicle (UAV) borne synthetic aperture radar (SAR) is more susceptible to motion errors in imaging, resulting in image quality degradation. More information can be provided for SAR imaging by using the separation of slant distance equations in the 3-D coordinate system. However, this method does not consider the problem of motion error compensation in UAV SAR imaging. In this paper, the phase error compensation of UAV mobile SAR imaging is studied. Combined with the sub-image segmentation, an improved modified Newton minimum entropy (MN-MEA) phase error compensation algorithm based on iterative block processing and the initial phase error model is proposed, which further corrects the residual spatiality error and motion error and improves the imaging quality.

Key words: unmanned aerial vehicle (UAV), synthetic aperture radar (SAR), phase error, minimum entropy

CLC Number: 

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