Star trackers, also known as star sensors or celestial navigation systems.actively determine a satellite’s orientation relative to stars using optical devices. Unlike GPS systems, which rely on Earth-based signals and may not function in deep space, star trackers utilize the fixed positions of stars as a reference framework. Consequently, they prove essential for satellites operating in low Earth orbit (LEO), geosynchronous orbit (GEO), or even interplanetary missions.
Optical Lens and Sensor: A wide-field or narrow-field lens pairs with a charge-coupled device (CCD) or complementary metal-oxide-semiconductor (CMOS) sensor to capture high-resolution images.
Processing Unit: An embedded computer actively runs algorithms for star identification, centroid calculation (precisely locating star centers), and attitude determination.
Baffle and Sunshade: These components block stray light from the sun, Earth, or other bright objects, which could disrupt star detection.
Satellites must maintain stable orientation to function effectively. Without precise attitude control, communication satellites fail to transmit signals accurately, or Earth observation satellites miss targets. Star trackers offer the highest accuracy among attitude sensors, surpassing gyroscopes, sun sensors, and Earth horizon sensors, especially when other references are absent.Furthermore, star trackers are highly resilient, effectively withstanding harsh space environments, such as radiation, extreme temperatures, and vacuum conditions.
Computational Demand: Processing star images in real-time requires significant onboard computing power, particularly for resource-constrained small satellites like CubeSats.
Space Radiation: Radiation may trigger single event upsets (SEUs) in electronics, leading to erroneous readings.
Cost Factors: High-precision star trackers cost anywhere from tens of thousands to hundreds of thousands of dollars, making them less feasible for low-budget missions.
The star tracker field rapidly evolves, driven by the booming satellite industry. Key advancements include miniaturization and integration, AI and machine learning, and multispectral capabilities, among others.
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