High-Precision Centroid Localization Algorithm for Star Sensor Under Strong Straylight Condition

Yuan, Jindong

doi:10.3390/rs17071108

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High-Precision Centroid Localization Algorithm for Star Sensor Under Strong Straylight Condition

2025-03-21

Yuan, Jindong

吴俊峰 (Junfeng Wu) *

Guohua Kang

DOI：10.3390/rs17071108

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Abstract

En 中文

Star sensor is disturbed by strong straylight, which increases the gray level of the captured star map, and this leads to invalid detection of star points and affects the high-precision location of the centroid. To address this issue, we propose a star centroid localization method based on gradient-oriented multi-directional local contrast enhancement. First, the background gray level distribution patterns of star sensors under various actual straylight interference conditions are analyzed. Based on this analysis, a background imaging model for complex operational scenarios is established. Finally, simulations are conducted under complex conditions with straylight images to test the star point detection rate, false detection rate, centroid localization accuracy, and statistical significance testing. The results show that the proposed algorithm outperforms the TOP-HAT, MAX-BACKG (Max-Background Filtering), LCM (Local Contrast Measure), MPCM (Multiscale Patch-Based Contrast Measure), and CMLCM (Curvature-Based Multidirectional Local Contrast Method for Star Detection of Star Sensor) algorithms in terms of star point detection rate. Additionally, the RMSE centroid localization error is achieved with 0.1 pixels, demonstrating its ability to effectively locate star centroids under complex conditions and meet certain engineering application requirements.

Keywords:

strong straylight

FACET

multi-directional gradient

centroid localization