## 1 Introduction  
With the characteristics of small size, flexible mobility, broad application scenarios, and low cost, unmanned aerial vehicles (UAVs) provide solid support for the construction of smart cities in the field of express logistics, smart agriculture, emergency rescue, remote sensing mapping [1, 2]. Satellite positioning is one of the main navigation technologies used in UAVs. Positioning and navigational accuracy have a great impact on the performance of UAVs, such as safety, stability, flexibility and attitude control [3]. However, the positioning and navigational accuracy are affected greatly by the low update frequency of receiver data. Traditionally, to obtain high-precision positioning data needs acquire enough epochs of data over a long time. Therefore, fast positioning generally cannot reach high accuracy. To improve the positioning accuracy of satellites, error sources need to be analyzed and compensated [4, 5]. There are many sources of positioning errors in GNSS, such as receiver clock error, satellite clock error, satellite orbit error, tropospheric error, etc. Due to the lack of reference information, the influence of various errors must be considered in the traditional single-point positioning method, and its positioning accuracy is from meter level to decimeter level. Studies show that the error of observation data between stations with short distances is similar [6], thus, using a station with a known accurate position as a reference station to differ the observation data between the reference station and the station close to it can eliminate most of the observation errors of the station and get high-precision positioning results in real-time. That is the core idea of RTK (Real Time Kinematic), a carrier-phase difference technology, that provides real-time three-dimensional positioning results with centimeter-level accuracy. Differential positioning can be divided into pseudo-range difference and carrier-phase difference according to the different types of observations. The pseudo-range difference is a differential processing of the pseudo-range observation, which can be positioned at an epoch moment with positioning accuracy of meters scale. The carrier-phase difference is a differential processing of the carrier phase observation, which can obtain a positioning accuracy of centimeters scale. Compared with pseudo-range signals, carrier-range signals are cosine waves without any markers, which will lead to the problem of unknown cycle ambiguities in receivers. In addition to the algorithm based on RTK, more powerful hardware and satellite receivers, etc., are also effective ways to improve linearity, positioning, and resolution. Moreover, increasing the number of satellite observations and extending the observation time can reduce the pathology of the parameter identification matrix and obtain precision integer ambiguity, which is commonly used in static poisoning for they need more than 1 h to observe enough data. To achieve fast accuracy positioning, this manuscript proposes to improve the success rate of the integer ambiguity solution. In fast positioning, unknown cycle calculation must be finished in several seconds or minutes with a few periods of observation data. However, the spatial structure of the satellites in a short time is of little change and great similarity. Thus, the ambiguity parameter identification matrix composed of these data is seriously ill-conditioned, which leads to great error or even unable to converge in the identification. There are two steps to get the integer ambiguity. The floating-point solution of integer ambiguity can be obtained first by identification. Then, the integer solution will be calculated by taking the floating-point solution as the initial value. Therefore, fast and accurate identification of the integer ambiguity is the key to improving positioning accuracy and is also the research focus in the field of GNSS position.