# A SLR Pre-Processing Algorithm Based on Satellite Signature Effect
## 1 Introduction  
Satellite laser ranging (SLR) is one of the high-precision fundamental space-geodetic technology to define the International Terrestrial Reference Frame (ITRF), which is important for the research on space exploration, environmental monitoring, urban construction, and other great topic studies. With the rapid development of the instruments in the terrestrial observation, the state-of-the-art SLR system can achieve sub-millimeter precision and obtain tens of thousands of annual observation passes [1; 2; 3].  
[PERSON] SLR system offers new possibilities for SLR data pre-processing algorithms. In 1984, normal point algorithm was first proposed [4], and now it has developed to be the standard pre-processing algorithm of international laser ranging service (ILRS) [5]. With the identification of satellite signature effect, the waveform of return signal is not assumed to be Gaussian distribution. On that basis, some corrections to the Normal point algorithm were proposed to satisfy the scientific demands for the Global Geodetic Observing System (GGOS) of mm precision ranging. In 1994, [PERSON] et al. first pointed out that the reflected signal is deformed and spread with a long tail in temporal distribution due to a satellite signature effect [6]. Then, [PERSON] et al. proved these results by simulationand laboratory tests [7]. Subsequently, [PERSON] et al. confirmed that a satellite signature effect could introduce the variations of mean SLR residuals of up to 15 mm [8]. In order to reduce the satellite signature effect on the SLR precision, [PERSON] et al. found a stable leading-edge level of the range residual distribution of AJISAI as a reference line to select the observation points [9], which improved the stability of normal points from 7.9 \(\pm\) 1.0 mm to 5.2 mm \(\pm\) 0.2 mm. In 2008, [PERSON] and [PERSON] modified the definition of the leading edge to the 10% of the nearest range residuals to further reduce the RMS of normal points [10]. In 2017, [PERSON] used Gaussian function to fit the front-only of SLR residual distribution and eliminated the desultory points based on the leading-edge-half-maximum (LEHM) method [11]. In most previous research, the satellite signature effect on ranging precision is regarded as a long-term statistical result of observations; the range error brought by the transient variation of return signal waveforms for different satellite orientation are always neglected. Thus, the instability of observational data for a short observation period caused by satellite signature effect did not have to be considered in the pre-processing algorithm, which would affect the final selection of the original observations for normal points and hinder the improvement of the range precision.  
In this paper, the conventional data processing for SLR system is simulated based on the revised model of satellite signature effect, which takes the structural and distribution characteristics of corner reflectors into account. A new clipping method is proposed and applied for SLR data processing of Changchun SLR station, by considering the systematic errors introduced by the variation of return signal in time for each observation. This paper enriches the theoretical models of SLR systematic errors and provides a valuable reference to minimize the influence of satellite signature effect on the SLR production.