基于卡尔曼滤波的实时总电子含量周跳探测与修复

总电子含量(total electron content, TEC)作为描述电离层形态和内部结构的重要参量,对于电离层领域的理论研究和发展有着重要作用,而周跳的探测一直以来都是全球定位系统(global position system, GPS)载波相位测量数据预处理的重点和难点,尤其是在高精度GPS定位中,卡尔曼(Kalman)滤波在周跳探测与修复中的应用使得能够准确可靠地探测出观测值中可能出现的周跳,利用Kalman滤波算法探测不同的观测数据类型及其组合,并将修复后的观测值与理论值进行对比。结果表明:该算法对周跳探测和修复有很强的有效性和精度。

Real-time TEC cycle slip detection and repair based on Kalman filter

As an important parameter describing the shape and internal structure of the ionosphere, Total Electron Content (TEC) plays an important role in the theoretical research and development of the ionosphere field. The detection of cycle slips has always been the focus and difficulty of Global Position System (GPS) carrier phase measurement data preprocessing, especially in In high-precision GPS positioning, the application of Kalman filtering in cycle slip detection and repair enables accurate and reliable detection of cycle slips that may appear in observations. Kalman filtering algorithm is used to detect different observation data types and combinations, and repair them The later observations are compared with theoretical values, and the results show that the algorithm has good effectiveness and accuracy for cycle slip detection and repair.