# New Satellite Selection Approach for GPS/BDS/GLONASS Kinematic Precise Point Positioning
## 1 Introduction  
Precise Point Positioning (PPP) is one of the recent techniques to make positioning efficient and cost effective by reducing labor and equipment costs for surveying [1]. It does not require any additional data from a reference station and can provide a solution with a centimeter to decimeter level of positional accuracy both in static and kinematic modes [2; 3]. Thus, PPP can be widely used in many fields such as vehicle navigation, mining survey, crustal motion, and coastal studies. With the development of global navigation satellite system (GNSS), PPP has attracted the attention of many scholars. [PERSON] et al. [4] applied the real-time multi-GNSS orbit and clock corrections of the CLK93 product released by Centre National d'Etudes Spatiales (CNES) for real-time multi-GNSS PPP processing, and its orbit and clock qualities were investigated. [PERSON] et al. [5] focused on the assessment of PPP in different systems. [PERSON] et al. [6] analyzed the impact of the solar flares on the GNSS-based navigation. [PERSON] and [PERSON] [7] studied the impact of the disturbances on the network RTK (real-time kinematic positioning) and PPP techniques. Currently, there are four constellations available, which include two full operational systems: Global Positioning System, GPS, and Globalnaya Navigazionnaya Sputnikovaya Sistema, GLONASS, and two systems still underconstruction: Galileo and BeiDou Navigation Satellite System, BDS. In detail, the GPS constellation comprises 31 operational Medium Earth Orbit (MEO) satellites flying in six orbital planes at an altitude of approximately 20,200 km as of 9 January 2019. GLONASS has recovered its full constellation since October 2011, with 24 satellites in three equally spaced orbital planes at an altitude of about 19,100 km [8]. The fully deployed Galileo system will consist of 30 MEO satellites (24 operational + six active spares) in three orbital planes at an altitude of 23,222 km [9]. The BDS will complete the constellation which will eventually have five Geosynchronous Earth Orbit (GEO), three Inclined Geosynchronous Satellite Orbit (IGSO), and 27 MEO satellites by 2020 [10; 11]. Now, there are 33 satellites in operation for BDS, more than GPS. Thus, compared with using only single GPS constellation, GNSS users can observe more visible satellites and obtain better reliability at the same time with the formation and improvement of the satellite constellations [12]. However, the improvement in positioning accuracy will become insignificant once the total number of satellites in view reaches a certain level. Tracking such a large number of visible satellites and processing the signals from all those satellites in a real-time kinematic process will put a heavy computational load on the receiver systems, especially for low-cost receivers [13]. In addition, it also causes excessive redundant information, which affects the real-time positioning performance of kinematic PPP services. Therefore, to quickly achieve the position, guarantee reliable positioning accuracy, and reduce the computing load of equipment, an appropriate data selection method is needed in the process of kinematic PPP. As a method that can effectively reduce the computational complexity and guarantee similar positioning accuracy with an original solution, the satellite selection algorithm is often used in Single Point Positioning (SPP), which causes us to consider its application in kinematic PPP. There are several mainstream satellite selection methods: the maximum volume algorithm [14], the optimal dilution of precision (DOP) algorithm [13; 15; 16; 17], the highest elevation angle satellite selection algorithm [18], and the fast-rotating partition satellite selection algorithm [19]. Recently, there have also been some studies devoted to satellite selection. [PERSON] et al. [20] introduced condition number of the design matrix in the reference satellite selection method to improve the structure of the normal equation. [PERSON] et al.