Nonuniformly-Rotating Ship Refocusing in SAR Imagery Based on the Bilinear Extended Fractional Fourier Transform

Area of Science:

• Remote Sensing
• Signal Processing

Background:

• Nonuniformly rotating ship refocusing is critical for satellite synthetic aperture radar (SAR) marine surveillance.
• Existing inverse SAR (ISAR) algorithms struggle with cross-terms and noise suppression for such targets.

Purpose of the Study:

• To propose a novel refocusing algorithm for nonuniformly rotating ships using satellite SAR data.
• To address the limitations of current ISAR-based parameter estimation methods.

Main Methods:

• Modeling ship signals as multicomponent cubic phase signals (CPS) after motion compensation.
• Utilizing the bilinear extended fractional Fourier transform (BEFRFT) for parameter estimation.
• BEFRFT estimates chirp rates and quadratic chirp rates of CPSs.

Main Results:

• The proposed BEFRFT algorithm demonstrates superior performance in suppressing cross-terms.
• BEFRFT shows excellent noise suppression capabilities for ship imaging.
• Effectiveness validated using simulated data and real Gaofen-3 satellite data.

Conclusions:

• The BEFRFT algorithm offers an effective solution for refocusing nonuniformly rotating ships in SAR imagery.
• This method significantly improves the quality of marine surveillance by enhancing ship imaging.
• BEFRFT provides a robust approach for parameter estimation in complex SAR scenarios.