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An enhanced cycle slip repair algorithm for real-time multi-GNSS, multi-frequency data processing

机译：用于实时多GNSS，多频数据处理的增强循环滑动修复算法

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摘要

Cycle slip detection and repair are crucial quality control steps in high-precision global navigation satellite system (GNSS) positioning using carrier phase measurements. Correct detection and repair of cycle slips can avoid repeated integer ambiguity resolution in real-time kinematic (RTK) or long convergence time in precise point positioning (PPP), especially in the context of multi-GNSS and multi-frequency cases. We introduce a generalized procedure for cycle slip detection and repair. The cycle slip detection is carried out using quality control theory on a single satellite-receiver pair. Upon successful detection, integer least-squares estimation is applied to repair the cycle slip vectors. Then if the cycle slips are detected but not repaired, and no cycle slip exists in the coming epochs, an enhanced repair algorithm, which uses measurements over multiple epochs, is developed. The mathematical model for cycle slip repair is strengthened to allow for higher success rate and its implementation is efficiently accomplished using Kalman filter to suit real-time applications. The generalized procedure and the enhanced algorithm for repair are theoretically analyzed for the dual- and triple-frequency cases under different elevations and ionospheric disturbances. Both high- and low-sampling rate MGEX data with artificial cycle slips are processed, and results indicate that the generalized procedure performs well in benign situations and a higher repair success rate is obtained by implementing the enhanced algorithm in extreme conditions.
机译：循环滑动检测和修复是使用载波相位测量的高精度全球导航卫星系统（GNSS）定位的重要质量控制步骤。循环滑动的正确检测和修复可以避免在精确点定位（PPP）中的实时运动（RTK）或长收敛时间中重复整数模糊分辨率，尤其是在多GNSS和多频率情况的上下文中。我们介绍了循环滑动检测和修复的广义手术。在单个卫星接收器对上使用质量控制理论进行循环滑动检测。在成功检测时，应用整数最小二乘估计来修复循环滑移矢量。然后，如果检测到循环滑动但未修复，并且在进入的时期中不存在循环滑动，则开发了使用多个时期使用测量的增强的修复算法。循环滑动修复的数学模型得到加强以允许更高的成功率，并且使用Kalman滤波器有效地实现其实现，以适应实时应用。在不同凸起和电离层扰动下的双频和三频案理论上，理论上分析了广义的方法和增强算法。处理具有人造循环滑动的高和低采样率MGEX数据，并且结果表明广义过程在良性情况下执行良好，并且通过在极端条件下实现增强算法来获得更高的修复成功率。

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