Joint detection-compensation method for ISAL images of spacecraft based on global image consistency

Area of Science:

• Optics and Photonics
• Signal Processing
• Remote Sensing Technology

Background:

• Vibration-induced phase errors degrade Inverse Synthetic Aperture Lidar (ISAL) imaging quality, particularly in low Signal-to-Noise Ratio (SNR) scenarios or without dominant scatterers.
• Existing compensation methods may struggle with complex vibration patterns or require specific target characteristics.

Purpose of the Study:

• To develop a robust joint detection-compensation framework for mitigating vibration-induced phase errors in ISAL.
• To enhance ISAL imaging quality, reduce false alarms, and improve contrast under adverse conditions.

Main Methods:

• A parametric model was developed to characterize sinusoidal vibration-induced phase modulation.
• A joint detection-compensation framework utilizing periodic feature extraction and spatio-temporal consistency was proposed.
• Vibration compensation was framed as a parameter inversion problem, processing full-aperture echoes directly.

Main Results:

• The proposed method significantly improved ISAL image quality compared to conventional approaches.
• Demonstrated effectiveness in suppressing false alarms and enhancing image contrast.
• Simulations on point and satellite targets confirmed the method's robustness and effectiveness.

Conclusions:

• The proposed joint detection-compensation framework offers a powerful solution for vibration compensation in ISAL systems.
• The method is effective even in low-SNR conditions and the absence of dominant scatterers.
• This approach enhances the practical applicability and performance of ISAL imaging.