Feasibility of Laser Communication Beacon Light Compressed Sensing

Area of Science:

• Optical Engineering
• Signal Processing
• Data Compression

Background:

• Laser Communication (LC) systems require efficient data handling for satellite-to-ground transmissions.
• Compressed Sensing (CS) offers potential bandwidth and storage savings but can degrade image quality for tracking.
• Traditional methods struggle with the trade-off between compression and tracking accuracy in LC beacon images.

Discussion:

• This study quantitatively assesses the feasibility of CS for light-spot tracking in LC systems.
• A redesigned measurement matrix optimizes CS for light-tracking requirements.
• A novel deep network, Compressed Sensing Denoising Center Net (CSD-Center Net), is developed for denoising and tracking from compressed data.

Key Insights:

• CS can significantly reduce bandwidth and storage requirements in LC systems (over 10x savings).
• The CSD-Center Net effectively denoises compressed images, enabling accurate light-spot tracking.
• Information preservation is directly correlated with the CS ratio; higher ratios retain more detail.

Outlook:

• CS with CSD-Center Net demonstrates feasibility for light-spot tracking in LC applications.
• Accuracy meets requirements for most scenarios when the data rate exceeds 10%.
• Further research can explore adaptive CS ratios and network optimizations for diverse LC environments.