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Star spot location estimation using Kalman filter for star tracker.

Hai-bo Liu¹, Jian-kun Yang, Jiong-qi Wang

¹College of Science, National University of Defense Technology, Changsha, Hunan, 41007, China.

|April 22, 2011

Summary

Accurate star spot location is crucial for star trackers. A Kalman filter approach improves star spot estimation by predicting locations, defining search windows, and updating measurements, effectively filtering noise.

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Area of Science:

Spacecraft attitude determination
Star tracker technology
Astrodynamics

Background:

Star tracker performance relies heavily on precise star spot location accuracy.
Inaccurate star spot identification directly impacts attitude determination precision.

Purpose of the Study:

To propose and validate a novel star spot location estimation approach for star trackers.
To enhance the accuracy and robustness of star trackers using a Kalman filter.

Main Methods:

A three-step Kalman filter-based method for star spot location estimation.
Prediction of approximate star spot locations in successive frames.
Utilizing small windows around predicted locations for measurement acquisition and Kalman filter updates.

Main Results:

Simulations using CHAMP satellite orbit data and a real guide star catalog were performed.
The proposed approach demonstrated significant noise filtering capabilities.
Effectiveness is contingent on maintaining a sufficient sampling frequency.

Conclusions:

The developed Kalman filter approach offers a robust solution for accurate star spot location estimation.
This method significantly improves the reliability of star trackers for attitude determination.
Sufficient sampling frequency is key to maximizing the noise reduction benefits.