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A Novel Joint Motion Compensation Algorithm for ISAR Imaging Based on Entropy Minimization.

Jishun Li1, Yasheng Zhang1, Canbin Yin1

  • 1Graduate School, Space Engineering University, Beijing 101416, China.

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|July 13, 2024
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Summary
This summary is machine-generated.

This study introduces a novel joint algorithm for Inverse Synthetic Aperture Radar (ISAR) motion compensation, enhancing imaging quality for high-speed space targets under low signal-to-noise ratio (SNR) conditions. The method effectively minimizes image entropy for improved accuracy.

Keywords:
entropy minimizationinverse synthetic aperture radar (ISAR)joint motion compensationnoise robustspace targets

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Area of Science:

  • Radar imaging
  • Signal processing
  • Astrodynamics

Background:

  • High-speed space targets require precise motion compensation for quality Inverse Synthetic Aperture Radar (ISAR) imaging.
  • Residual errors from high-speed motion compensation (HSMC) degrade translational motion compensation (TMC) accuracy.
  • Low signal-to-noise ratio (SNR) further challenges the accuracy of both HSMC and TMC.

Purpose of the Study:

  • To propose a joint ISAR motion compensation algorithm optimized for low-SNR environments.
  • To address the coupled errors between HSMC and TMC in space target imaging.
  • To enhance the accuracy and robustness of ISAR imaging for fast-moving targets.

Main Methods:

  • Modeling space target motion as a high-order polynomial to establish a joint compensation model.
  • Utilizing entropy minimization as the objective function for motion parameter estimation.
  • Employing the red-tailed hawk-Nelder-Mead (RTH-NM) algorithm for parameter estimation and joint compensation.

Main Results:

  • The proposed joint algorithm effectively compensates for both high-speed and translational motion under low SNR.
  • Experimental results with simulated and real data demonstrate significant improvements in ISAR image quality.
  • The algorithm shows robustness in handling residual errors and low signal conditions.

Conclusions:

  • The developed joint ISAR motion compensation algorithm offers a robust solution for high-quality imaging of space targets.
  • Entropy minimization combined with the RTH-NM algorithm provides an effective approach for parameter estimation in challenging SNR conditions.
  • This work advances ISAR imaging capabilities for space surveillance and reconnaissance applications.