A highly adaptable method for GNSS cycle slip detection and repair based on Kalman filter
A highly adaptable method for GNSS cycle slip detection and repair based on Kalman filter
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基于卡尔曼滤波器的高适应性GNSS周跳检测与修复方法
DOI：
10.1080/00396265.2020.1756107
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发表时间：
2020-04
期刊：
影响因子：
1.6
通讯作者：
Xia Siqi
中科院分区：
文献类型：
--
作者：
Yu Xianwen;Xia Siqi
周跳检测与修复是GNSS载波相位观测数据预处理的关键步骤。然而，目前能够满足多种情况下数据处理需求的周跳检测与修复方法很少。为了解决这一问题，提出了一种高适应性的周期滑移检测与修复方法。首先，利用伪距离和载波双差分（DD）观测值建立周跳检测方程；建立了基于星地距离的状态方程。然后，将这两个方程结合起来，建立了卡尔曼滤波估计模型。随后，可以检测和修复周期滑移。最后，根据条件分布对状态参数进行细化。根据算例的结果，利用所提出的方法对所有模拟的循环滑移进行了检测和修复。结果表明，该方法可以满足多种情况下的数据处理需求。
The cycle slip detection and repair are crucial steps in the preprocessing of GNSS carrier phase observation. Currently, however, there are few cycle slip detection and repair methods that can meet the data processing needs for diverse situations. To solve this problem, a highly adaptable cycle slip detection and repair method is proposed. First, a cycle slip detection equation is established using the pseudo-range and carrier double-differenced (DD) observations; the state equation is developed based on the satellite-ground distance. Then, a Kalman filter estimation model is established by joining the two equations. Subsequently, the cycle slip can be detected and repaired. Finally, the state parameters are refined in accordance with the conditional distribution. According to the results of the example, all the simulated cycle slips are detected and repaired by the method proposed. It shows that the method can meet the data processing needs for multiple situations.
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