Robustness Study of Non-Dimensional Star Pattern Recognition for a Typical Star Tracker

The Non-Dimensional star pattern recognition algorithm is known to be independent of image Focal Length and Optical axis offset but this independency doesn’t mean that the algorithm conserves it’s robustness in presence of any type of errors. These errors arise from poor hardware calibration and software inaccuracy which causes the algorithm’s input to be different from the true amount stored in the database. The effect of bright point position errors on pattern feature is modeled. The monte-carlo simulation method is used to evaluate the algorithm’s performance for different amounts of error. Results demonstrate that 0.1 Pixel size error is admissible to conserve the trade-off between valid update frequency, hardware accuracy and algorithm’s robustness.