Inverse synthetic aperture ladar autofocus imaging algorithm for micro-vibrating satellites based on two prominent...

Area of Science:

• Remote Sensing
• Optical Engineering
• Signal Processing

Background:

• Inverse Synthetic Aperture Ladar (ISAL) is crucial for high-resolution imaging of long-range satellite targets.
• Satellite micro-vibrations, comparable to ISAL wavelengths, cause image defocusing, necessitating motion compensation.

Purpose of the Study:

• To propose a novel autofocus algorithm for ISAL.
• To estimate and compensate for phase errors caused by translational and rotational micro-vibrations.

Main Methods:

• Development of a new autofocus algorithm based on two prominent points.
• Comparison with existing algorithms: Phase Gradient Autofocus (PGA), contrast-based, and entropy-based autofocus.

Main Results:

• The proposed algorithm demonstrates effectiveness in compensating for rotational phase errors with multiple oscillations.
• Simulations and experimental validation confirm the algorithm's feasibility.

Conclusions:

• The novel two-prominent-point autofocus algorithm significantly improves ISAL image quality.
• This method offers a robust solution for motion compensation in satellite imaging applications.