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A Fourier-Based Image Formation Algorithm for Geo-Stationary GNSS-Based Bistatic Forward-Looking Synthetic Aperture

Zhangfan Zeng1, Zhiming Shi2, Sainan Xing3

  • 1School of Computer Science and Information Engineering, Hubei University, Wuhan 430062, China. zengzhangfan@hotmail.com.

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This study introduces a novel image formation algorithm for Geo-Stationary GNSS-based Bistatic Forward-Looking Synthetic Aperture Radar (GeoSta-GNSS-BFLSAR) systems. Simulations confirm the algorithm

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GNSSforward looking SARimage formation

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Area of Science:

  • Remote Sensing
  • Radar Systems
  • Signal Processing

Background:

  • Passive bistatic synthetic aperture radar (SAR) systems offer unique advantages for surveillance and navigation.
  • Geo-Stationary GNSS-based Bistatic Forward-Looking SAR (GeoSta-GNSS-BFLSAR) is an emerging passive bistatic SAR system with potential applications in self-landing, navigation, and battlefield intelligence.
  • Limited research exists on the image formation and performance of GeoSta-GNSS-BFLSAR systems.

Purpose of the Study:

  • To propose and validate a preliminary image formation algorithm for GeoSta-GNSS-BFLSAR systems.
  • To analytically discuss the system's performance, including focusing depth and spatial resolution.
  • To address challenges such as long dwell time and spatial variance inherent in GeoSta-GNSS-BFLSAR.

Main Methods:

  • Development of a modified migration correction factor to handle long dwell times and spatial variance.
  • Analytical derivation of mathematical models for image formation and system performance.
  • Conducting simulations to verify the proposed algorithm, focusing depth, and spatial resolution.

Main Results:

  • The proposed image formation algorithm demonstrates focusing performance highly similar to theoretical predictions.
  • Analytical discussions provide insights into the system's focusing depth and spatial resolution limitations.
  • Simulations validate the feasibility of the GeoSta-GNSS-BFLSAR concept at a simulation level.

Conclusions:

  • The developed algorithm effectively addresses the challenges of GeoSta-GNSS-BFLSAR, proving its simulation-level feasibility.
  • This work lays the groundwork for future real-world applications of GeoSta-GNSS-BFLSAR technology.
  • Further research can build upon these findings to refine the system for practical deployment.