Sparse Autofocus Method for Maneuvering Platform High-squint SAR Based on Two-dimensional Spatial-variant Motion Compensation

Gen LI; Yanheng MA; Xuying XIONG

doi:10.11999/JEIT200456

Volume 43 Issue 7

Jul. 2021

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Gen LI, Yanheng MA, Xuying XIONG. Sparse Autofocus Method for Maneuvering Platform High-squint SAR Based on Two-dimensional Spatial-variant Motion Compensation[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1992-1999. doi: 10.11999/JEIT200456

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Gen LI, Yanheng MA, Xuying XIONG. Sparse Autofocus Method for Maneuvering Platform High-squint SAR Based on Two-dimensional Spatial-variant Motion Compensation[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1992-1999. doi: 10.11999/JEIT200456

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Sparse Autofocus Method for Maneuvering Platform High-squint SAR Based on Two-dimensional Spatial-variant Motion Compensation

doi: 10.11999/JEIT200456

Department of UAV Engineering, Army Engineering University Shijiazhuang Campus, Shijiazhuang 050003, China

Received Date: 2020-06-08
Rev Recd Date: 2020-11-29

Available Online: 2020-12-02

Publish Date: 2021-07-10

Abstract

Abstract

The existence of high-squint angle and three-dimensional acceleration makes the motion error of maneuvering platform SAR have obvious two-dimensional spatial variability, which greatly increases the difficulty of imaging. A sparse autofocus method based on the estimation and compensation of two-dimensional spatial-variant motion error is proposed. Based on the Keystone transform and the frequency domain phase filtering method, a frequency-domain approximate observation operator is constructed to correct the spatial-variant imaging parameters. In the process of autofocus, firstly, a sparse autofocus model based on the frequency-domain approximate observation operator is constructed to focus the image roughly and estimate the non-spatial-variant motion error parameters, and the Iterative Shrinkage-Thresholding Algorithm (ISTA) is used to solve the constructed sparse autofocus model. Then, the precise phase error curves of multiple sub-regions are obtained by the sparse autofocus model and the least square method can be used to estimate the spatial-variant motion error parameters. Finally, the compensation of spatial-variant motion error is realized by correcting the approximate observation operator. The simulation results show the effectiveness of the proposed method.
- SAR,
- High-squint,
- Maneuvering platform,
- Two-dimensional spatial-variant motion error,
- Sparse autofocus

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References(17)

References

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