An Improved Parametric Polar Format Algorithm for Missile-Borne SAR Imaging With a Dive and Curve Trajectory

Due to the two-dimensional spatial variability of the range model during the missile-borne synthetic aperture radar (SAR) flight along a dive and curve trajectory, the accuracy of traditional algorithms is limited. In this paper, a new improved parametric polar format algorithm (IPPFA) is proposed to process missile-borne SAR imaging with a dive and curve trajectory. The algorithm divides the trajectory into two parts: dive trajectory and curve trajectory. For the dive trajectory processing, a new imaging coordinate system is established to transform the dive trajectory into a horizontal trajectory through coordinate rotation, and the space variation scene height change error term caused by coordinate rotation is embedded into the range variation compensation of the PPFA algorithm. Then, for the curve trajectory processing, based on the precise motion compensation ability of PPFA algorithm, we regard the curve trajectory caused by acceleration as the equivalent quadratic motion error that can be accurately analyzed, and then the equivalent motion error is processed through azimuth interpolation in PPFA. In addition, using the advantage that the equivalent motion error can be accurately expressed analytically, we derive a more accurate space-time spectral relationship to ensure the accuracy of wavefront curvature compensation. Finally, the superiority and effectiveness of the proposed algorithm are verified by comparing the simulation and real-data experiments with other imaging algorithms.

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Publication Details

Journal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/jstars.2025.3581574
Primary Topic
Advanced SAR Imaging Techniques
Type
article
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article

An Improved Parametric Polar Format Algorithm for Missile-Borne SAR Imaging With a Dive and Curve Trajectory

Guanyong Wang, Zhichao Meng, Xinshuo Wang, Jingyue Lu et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Advanced SAR Imaging Techniques
article

An Improved Parametric Polar Format Algorithm for Missile-Borne SAR Imaging With a Dive and Curve Trajectory

Guanyong Wang, Zhichao Meng, Xinshuo Wang, Jingyue Lu, Zirui Xi, Lei Zhang
article en

Abstract

Due to the two-dimensional spatial variability of the range model during the missile-borne synthetic aperture radar (SAR) flight along a dive and curve trajectory, the accuracy of traditional algorithms is limited. In this paper, a new improved parametric polar format algorithm (IPPFA) is proposed to process missile-borne SAR imaging with a dive and curve trajectory. The algorithm divides the trajectory into two parts: dive trajectory and curve trajectory. For the dive trajectory processing, a new imaging coordinate system is established to transform the dive trajectory into a horizontal trajectory through coordinate rotation, and the space variation scene height change error term caused by coordinate rotation is embedded into the range variation compensation of the PPFA algorithm. Then, for the curve trajectory processing, based on the precise motion compensation ability of PPFA algorithm, we regard the curve trajectory caused by acceleration as the equivalent quadratic motion error that can be accurately analyzed, and then the equivalent motion error is processed through azimuth interpolation in PPFA. In addition, using the advantage that the equivalent motion error can be accurately expressed analytically, we derive a more accurate space-time spectral relationship to ensure the accuracy of wavefront curvature compensation. Finally, the superiority and effectiveness of the proposed algorithm are verified by comparing the simulation and real-data experiments with other imaging algorithms.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingVol. 18
North China University of Technology (CN), Xidian University (CN), Sun Yat-sen University (CN)
Openalex Percentile: Top 81%
Advanced SAR Imaging Techniques
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