Multiexposure imaging and parameter optimization for intensified star trackers.

Area of Science:

• Aerospace Engineering
• Optical Instrumentation
• Astrodynamics

Background:

• Intensified star trackers offer improved dynamic performance but face limitations in attitude update rates due to pixel data processing.
• Existing exposure imaging methods restrict the speed at which attitude information can be updated.

Purpose of the Study:

• To propose a novel multi-exposure imaging approach for intensified star trackers to overcome attitude update rate limitations.
• To enhance the signal-to-noise ratio (SNR) for dim stars by accumulating energy across multiple exposures.
• To optimize the parameters of the multi-exposure approach for maximum performance.

Main Methods:

• A multi-exposure imaging technique is developed, where a single image captures N distinct star positions.
• A motion model of star spots in the image plane is established to guide parameter optimization.
• Simulations and experimental validation are conducted to assess the approach's effectiveness.

Main Results:

• The multi-exposure approach achieves an N-fold increase in attitude update rate compared to conventional methods.
• Dim star detection is improved due to enhanced signal-to-noise ratio via energy accumulation.
• Optimized parameters lead to superior performance of the intensified star tracker.

Conclusions:

• The proposed multi-exposure imaging approach significantly boosts the attitude update rate of intensified star trackers.
• This technique offers a viable solution for improving star tracker performance, especially for dim celestial objects.
• Parameter optimization is crucial for realizing the full potential of the multi-exposure imaging method.