4.7 Article

Focusing Translational-Variant Bistatic Forward- Looking SAR Data Using the Modified Omega-K Algorithm

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2021.3063780

Keywords

Azimuth; TV; Synthetic aperture radar; Doppler effect; Receivers; Geometry; Focusing; Bistatic omega-K algorithm; space variance; translational-variant bistatic forward-looking synthetic aperture radar (TV BFSAR)

Funding

  1. National Key Research and Development Program of China [2018YFB2202500]
  2. National Natural Science Foundation of China [61001211, 61303035, 61471283]
  3. Key Research Program of Shaanxi [2016MSZD-S-14-3]

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This article focuses on accurate 2-D frequency spectrum issues in translational-variant bistatic forward-looking synthetic aperture radar with curved trajectory, proposing a modified omega-K imaging algorithm and introducing methods such as linear range cell migration correction and high-order polynomial fitting, while compensating for spatial-variant Doppler parameters through azimuth resampling.
Accurate 2-D frequency spectrum (2-D FS) with acceleration, two-way range coupling terms, and spatial-variant Doppler parameters are the main problems to be solved in translational-variant bistatic forward-looking synthetic aperture radar (SAR) (TV BFSAR) with curved trajectory. For these issues, a modified omega-K imaging algorithm is derived in this article. The maximum usage of 2-D FS based on the method of series reversion (MSR) is achieved by linear range cell migration correction, and 2-D FS is linearized in bistatic range by using high-order polynomial fitting. Then, a method of azimuth resampling is introduced to implement compensation of spatial-variant Doppler parameters. Different from other bistatic omega-K methods, our newly proposed method focuses on the small-aperture data in the azimuth frequency domain to avoid azimuth aliasing without padding zeros and uses the frequency focusing position to study the model of spatial-variant phase. Simulation results and real data verify the effectiveness of the proposed method.

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