基于多历元递推最小二乘卡尔曼滤波方法的模糊度解算

Ambiguity Resolution Based on Recursive Least Squares Kalman Filtering Using Multi-epoch Carrier Phase Data

  • 摘要: 针对GPS动态定位,通过使用递推最小二乘技术,提出基于递推最小二乘的仅含有模糊度参数的卡尔曼滤波方法,实现了利用多历元载波相位观测信息解算模糊度。同时针对多历元定位的特点,讨论了动态定位中的单频周跳探测与修复,并提出将卫星重新出现的情况按照周跳的处理方法,有效地提高了解算效果。

     

    Abstract: In the global positioning system(GPS) kinematic positioning,the pseudorange and carrier phase measurements are often used together to calculate the carrier phase integer ambiguity.The pseudorange information can be either a raw observation of a single epoch or a smoothed value based on multi-epoch.For the carrier phase information,traditionally only single-epoch observations are used,because the position of the GPS antenna changes continuously in kinematic applications.A new carrier phase ambiguity resolution method is proposed by using multi-epoch data for both pseudorange and carrier phase data.First,the recursive least squares method is introduced,which can build the observation equations with the information from a continuous data segment.Next,a Kalman filter based on the only ambiguity state is used to calculate the float ambiguities.Then,the cycle slip detection and repair technique in kinematic mode is discussed with special emphasis on bridging discontinuous observations.The proposed method offers an obvious computational and performance advantage.The experiment proves that the proposed method can efficiently solve the integer ambiguities in GPS kinematic positioning.

     

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