Abstract: The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is widely used in mapping and monitoring the changes of ice sheets and forest vegetation. However, the satellite receives all the photons returning from around 532 nm, including surface signal photons and atmospheric noise photons, which means that the acquisition of surface information and high-level products is limited by the large proportion of noise photons. Therefore, onboard filtering is required on the satellite to identify the position of the signal photons. In this article, we propose a simple and effective onboard filtering algorithm that does not require any prior terrain information. Based on 1 019 954 major frames of data, the processing time, data volume, and signal recognition accuracy were calculated, and the impacts of five influencing factors (time of day, land cover, solar elevation, surface slope, and beam strength) on the algorithm were evaluated. The results showed that the processing time was lower compared with existing algorithms, the average ratio of all the major frame ranges was 0.8234, and 98.69% of the areas that originally included the signal could also be identified. Subsequent evaluations found that the selected solar elevation and surface slope have the greatest impact on the accuracy of the algorithm. The proposed no-prior-terrain onboard filtering algorithm represents an effective means for obtaining the telemetry range from ICESat-2 altimetry data, to address the challenges of onboard storage and satellite ground transmission.
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