采用电离层权重的长距离网络RTK参考站间模糊度解算方法

LONG BASELINE NETWORK RTK AMBIGUITY RESOLUTION USE OF IONOSPHERE-WEIGHTED MODEL

针对常规电离层权重法解算模糊度需要电离层先验信息的局限性,提出了一种基于改进电离层权重模型的网络RTK参考站间模糊度解算方法。该方法先利用相位平滑伪距构造电离层伪观测量及相应随机模型;再建立基于电离层权重的卡尔曼滤波模型;最后引入自适应卡尔曼滤波算法,调节补偿由于滤波模型不准确对估计参数值造成的偏差。算例分析表明,该方法可适用于长距离网络RTK参考站间模糊度解算,特别对于仰角在20°以上卫星模糊度解算收敛快,稳定性较好。

Ambiguity resolution based on conventional ionosphere-weighted model usually needs prior information about ionoshperic delay. A new ambiguity resolution for network RTK based on improved ionosphere-weighted model is proposed for the situation without prior information. Firstly,the ionospheric pseudo-observations and stochastic model are constructed through carrier-smoothed code. Then,the Kalman filter mode based on ionosphereweighted function is established. at last,the adaptive Kalman filter algorithm is introduced,so as to adjust parameters evaluation tolerance caused by model inaccuracy. Experiment shows that this new method possesses fast convergence and well stability. It is suitable to long-range network RTK,particularly to the satellites with 20°or more elevation angle.