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Updated: Sep 5, 2025

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An Adjusted Frequency-Domain Algorithm for Arc Array Bistatic SAR Data with One-Moving Transmitter.

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  • 1College of Information Engineering, Inner Mongolia University of Technology, Hohhot 010051, China.

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Summary
This summary is machine-generated.

Arc array bistatic synthetic aperture radar (AA-BiSAR) offers improved concealment and system flexibility. A novel range frequency-domain algorithm effectively processes AA-BiSAR data, enhancing imaging capabilities.

Keywords:
arc array antennafrequency-domainkeystone transformsynthetic aperture radarthe spatial resolution

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Area of Science:

  • Remote Sensing
  • Radar Systems
  • Signal Processing

Background:

  • Traditional arc array synthetic aperture radar (AA-SAR) provides multi-directional observation but suffers from poor concealment.
  • Bistatic synthetic aperture radar (SAR) configurations can enhance system flexibility and expand imaging scenes.

Purpose of the Study:

  • To propose and validate a novel imaging algorithm for arc array bistatic synthetic aperture radar (AA-BiSAR) with a moving transmitter.
  • To address the concealment limitations of traditional AA-SAR while maintaining or improving imaging performance.

Main Methods:

  • Establishment of the imaging geometry and signal model for AA-BiSAR.
  • Development of a range frequency-domain algorithm utilizing Taylor series expansion and Keystone Transform (KT).
  • Compensation for residual phase errors due to transmitter motion and elimination of range cell migration.

Main Results:

  • The proposed algorithm effectively focuses AA-BiSAR data, producing a clear image.
  • Simulation results demonstrate the algorithm's effectiveness and analyze the impact on spatial resolution.
  • The AA-BiSAR system with the proposed algorithm shows advantages in concealment and flexibility.

Conclusions:

  • The developed range frequency-domain algorithm is effective for AA-BiSAR imaging.
  • AA-BiSAR offers a promising solution for enhanced concealment and system flexibility in SAR applications.
  • Further analysis of spatial resolution characteristics is crucial for system optimization.