基于卡尔曼滤波的多径误差消除及双频模糊度快速估计方法研究

Study on Multipath Mitigation and Dual-frequency Fast Ambiguity Estimation Based on Kalman Filter

伪距多径误差的存在使得单历元确定宽巷模糊度可靠性不高。为此,该文提出了一种用卡尔曼滤波实现宽巷模糊度与多径误差实时分离的方法。此方法将多径误差作为一阶高斯马尔可夫过程,在估计宽巷模糊度的同时也将多径误差求解出来,实现了伪距多径误差与宽巷模糊度的实时分离,可在短时间内得到模糊度的可靠值。文中用不同基线长度的实际观测数据进行了实验分析,实验结果证明了该方法的正确性及可靠性。

The low reliability of estimation to widelane ambiguity is mainly caused by pseudo-range multipath error Therefor, a new method based on Kalman filter is proposed to separate multipath error from widelane ambiguity in real time. This method can get reliable ambiguity in short time when the multipath error is modeled as first order Ganss-Markov process. The validity and reliability of proposed method are confirmed with experiments.