Segmentation processing technology for weak signal data in lunar laser ranging

Astronomical Techniques and Instruments

卷:3

Article

Qiang Qian¹  Chengkai Zhou¹  Xida Han^1,2  Xianlin Wu¹  Xudong Lin¹  Ming Li¹  Hongchao Zhao³ 

[1] School of Advanced Manufacturing, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China

[2] National Gravitation Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China

[3] MOE Key Laboratory of TianQin Mission, TianQin Research Center for Gravitational Physics & School of Physics and Astronomy, Frontiers Science Center for TianQin, Gravitational Wave Research Center of CNSA, Sun Yat-sen University (Zhuhai Campus), Zhuhai 519082, China

关键词: Lunar laser ranging;    Low signal-to-noise ratio;    Segmentation integration method;    Signal existence verification;   

DOI  :  10.3724/ati2025074

 received in 2025-09-08, accepted in 2025-12-10,  发布年份 2026

来源: Tianwenyanjiu

【 摘 要 】

When performing Lunar Laser Ranging (LLR), the signal within the echo data is often submerged by noise. Sometimes, only a fraction of suspected signals can be detected, making signal extraction a challenging task, and even if the suspected signals are successfully extracted, it remains uncertain whether the extracted data accurately represent 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, and the characteristic parameters of the data distribution are compared to verify the authenticity of the extracted signals. When processing actual measurement data, a comparison is made with the classical Poisson filtering algorithm. The segmented integration signal extraction method is experimentally confirmed to show 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.

【 授权许可】

CC BY-NC-ND   
© 2026 Editorial Office of Astronomical Techniques and Instruments, Yunnan Observatories, Chinese Academy of Sciences.

【 图 表 】

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