顾及卫星空间分布状态的GNSS信噪比随机模型

GNSS signal-to-noise ratio stochastic model considering satellite spatial distribution

为了研究随机模型对GNSS定位精度的影响,介绍了GPS/GLONASS/BDS组合伪距单点定位的函数模型以及几种当前常用的先验随机模型。结合各个模型的优缺点,提出通过指数函数引入空间分布改善因子,建立一种改进的信噪比随机模型,并设计相关多系统伪距单点定位试验对其性能进行分析。实验结果表明:改进模型的解算精度显著优于现存的几种先验随机模型,相比等权模型在三维定位精度上提升15%~30%,相比高度角模型提升15%~25%,相比信噪比模型提升5%~15%,相比现存的PDOP模型也有明显提升。改进模型在不同遮蔽情况、双系统和三系统组合定位时精度均优于现存的信噪比随机模型,从而验证了该定权算法的有效性。

In order to study the influence of stochastic model on GNSS positioning accuracy,the functional model of GPS/GLONASS/BDS combined standard point positioning and several commonly used prior stochastic models are briefly introduced.Combining the advantages and disadvantages of each model,an improved stochastic model of signal-to-noise ratio is established by introducing spatial distribution improvement factor through exponential function,and the performance of the model is analyzed by multi-GNSS standard point positioning test.The results of test showed that the accuracy of the proposed model is significantly higher than that of the existing prior stochastic models.Compared with the equal-weight model,the three-dimensional positioning accuracy of the proposed model is improved by 15%~30%,corresponding to the elevation mask model by 15%~25%,corresponding to the signal-to-noise ratio model by 5%~15%,and it’s also significantly improved compared with the existing PDOP model.The accuracy of the proposed model is better than that of the existing SNR stochastic model in different occlusion conditions,dual-system and triple-system combination positioning,which verifies the effectiveness of the weighting algorithm.