Fine-filter method for Raman lidar based on wavelength division multiplexing and fiber Bragg grating

Area of Science:

• Atmospheric Science
• Optical Remote Sensing
• Spectroscopy

Background:

• Atmospheric temperature is crucial for understanding atmospheric state, dynamics, and thermodynamics.
• Rotational Raman scattering is a key technique for atmospheric temperature monitoring.
• Existing methods face challenges with background noise and signal utilization.

Purpose of the Study:

• To present a novel fine-filter method for atmospheric temperature monitoring.
• To improve the precision and signal-to-noise ratio of remote sensing.
• To provide a stable and miniaturized filter system for space-based applications.

Main Methods:

• A fine-filter method based on wavelength division multiplexing and fiber Bragg grating in the visible spectrum.
• Secondary cascaded light paths to filter background noise.
• Passive temperature compensation for fiber Bragg grating stability.

Main Results:

• Enhanced detection intensity and signal-to-noise ratio by optimizing return signal utilization.
• Reduced temperature sensitivity of the fiber Bragg grating.
• Demonstrated a feasible solution for miniaturized, high anti-interference, and stable filter systems.

Conclusions:

• The proposed fine-filter method offers a significant advancement in atmospheric temperature remote sensing.
• The system exhibits high performance suitable for space-based platforms.
• This approach enhances the understanding of atmospheric parameters through improved monitoring capabilities.