Research on Segmentation Processing Technology of Weak Signal Data in Laser Ranging

When performing Lunar Laser Ranging (LLR) at laser ranging stations, the signal within the echo data is often submerged in noise. Only some suspected signals can be detected, making signal extraction a challenging task. Even if the suspected signals are successfully extracted, it remains uncertain whether the extracted data truly represents the real signal. This study proposes a segmented-integration signal extraction method. By taking the intervals where the residual signals are present as a priori conditions, time intervals containing suspected signals are identified. The data within these intervals are then integrated and processed. To verify the authenticity of the extracted signals, the characteristic parameters of the data distribution are compared. When processing actual measurement data, a comparison is made with the classical Poisson filtering algorithm. The experimental results demonstrate that the segmented-integration signal extraction method exhibits better performance when dealing with ranging data containing suspected signals; based on the characteristic parameters of the data distribution, the existence of real signals can be effectively verified.