The geostationary orbit (GEO), about 35,786 km above the Earth’s equator, hosts high-value satellites like communication, meteorological, and navigation ones. Real-time detection of geostationary orbit targets is crucial for orbital resource safety and satellite operation. Large field-of-view (FOV) telescopes can observe many such targets but face technical bottlenecks due to their optical systems, such as weak light-gathering capability, stellar interference, and complex stray light. This paper analyzes the apparent motion differences between stars and geostationary orbit targets based on the telescope’s staring mode. Stars move overall in images while GEO targets are relatively stationary. A minimum value stacking (Min-Stacking) method is proposed to suppress stars, improving GEO targets’ signal-to-noise ratio. With the global threshold segmentation algorithm, fast and accurate target extraction is achieved. Experiments show the method has high detection rates, overcomes interference, and features simplicity and real-time performance, with important application value.
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