北斗观测量时间相关随机模型构建及评估

Construction and evaluation of time-dependent stochastic model for BDS observation

传统多历元累积观测量随机模型通常忽略各历元间观测量的时间相关性,导致其对观测量整体随机特性刻画不准确。考虑北斗系统中GEO卫星观测量的时间相关性较强,本文提出一种适用于多历元下北斗观测量的时间相关随机模型构建方法。在传统多历元随机模型的基础上,将时间相关系数直接引入随机模型,通过观测量站间差分残差计算各历元间观测量的时间相关系数,生成多历元下北斗观测量时间相关随机模型,并利用实际试验数据对其在整周模糊度解算中的表现进行评估。试验结果表明,时间相关随机模型在一定程度上解决了传统随机模型存在的整周模糊度PCF下限估值虚高的问题,提高了整周模糊度Ratio值,有助于整周模糊度顺利通过检验。此外,相比于传统随机模型,时间相关随机模型有效减少了整周模糊度漏检及误警的情况出现,提高了整周模糊度解算的可靠性。

The traditional multi-epoch cumulative observational stochastic model usually ignores the time correlation of observations between epochs,which leads to its inaccurate characterization of the overall stochastic characteristics of observations.Considering the strong time correlation of GEO satellite observations in the BeiDou system,this paper proposes a method for constructing a timedependent stochastic model suitable for BeiDou observations in multiple epochs.Based on the traditional multi-epoch stochastic model,the time correlation coefficient is directly introduced into the stochastic model,and the time correlation coefficient of each epoch observation is calculated by the residual after the difference between observation stations,and time-dependent stochastic model of BDS observation measurement under multi-epoch accumulation is generated,and its performance in integer ambiguity resolution is evaluated by actual experimental data.The experimental results show that the time-dependent stochastic model solves the problem of the overestimation of the lower limit of the PCF for the integer ambiguity in the traditional stochastic model to some extent,improves the Ratio value of integer ambiguity,and helps the integer ambiguity to pass the detection successfully.In addition,compared with the traditional stochastic model,the time-dependent stochastic model can effectively reduce the occurrence of missed detection and false alarm of integer ambiguity,and improves the reliability of integer ambiguity resolution.