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A Novel General Imaging Formation Algorithm for GNSS-Based Bistatic SAR.

Hong-Cheng Zeng1, Peng-Bo Wang2,3, Jie Chen4,5

  • 1School of Electronic and Information Engineering, Beihang University, Beijing 100191, China. zenghongcheng@buaa.edu.cn.

Sensors (Basel, Switzerland)
|March 2, 2016
PubMed
Summary
This summary is machine-generated.

A new algorithm focuses Global Navigation Satellite System (GNSS)-based bistatic Synthetic Aperture Radar (SAR) data efficiently. This method avoids interpolation, improving remote sensing accuracy and real-time global coverage capabilities.

Keywords:
GNSSbistatic SARbulk RCMCmodified hybrid correlation

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Area of Science:

  • Remote Sensing
  • Geophysics

Background:

  • Global Navigation Satellite System (GNSS)-based bistatic Synthetic Aperture Radar (SAR) is increasingly vital for remote sensing due to its cost-effectiveness and global coverage.
  • Traditional back projection algorithms (BPAs) for GNSS-based bistatic SAR data often involve complex interpolation, impacting efficiency.

Purpose of the Study:

  • To propose a general imaging formation algorithm for accurate and efficient focusing of GNSS-based bistatic SAR data.
  • To avoid interpolation processing inherent in traditional BPAs.

Main Methods:

  • A two-dimensional point target spectrum model was developed.
  • Bulk range cell migration correction (RCMC) was derived to reduce range cell migration (RCM) and achieve coarse focusing.
  • A modified hybrid correlation operation was introduced to compensate for residual phase errors after bulk RCMC.

Main Results:

  • The proposed algorithm successfully focuses GNSS-based bistatic SAR data without interpolation.
  • Simulation results demonstrated satisfactory performance under general geometric conditions, including non-parallel trajectories and unequal platform velocities.
  • The method effectively reduces range cell migration and compensates for phase errors.

Conclusions:

  • The developed imaging formation algorithm offers an accurate and efficient solution for processing GNSS-based bistatic SAR data.
  • This approach enhances the applicability of GNSS-based bistatic SAR in remote sensing by improving data processing.
  • The method shows promise for real-time global coverage applications.