卫星导航信号与定位目标信号时延估计
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摘要
卫星导航信号与定位目标信号在电离层及对流层的传播时延是全球导航卫星系统(Global Navigation Satellite System,GNSS)定位的重要误差源。对这类信号传播时延进行估计,是改善系统定位精度的重要手段。常规的时延估计方法根据霍普菲尔德、萨斯塔莫宁等经验模型计算信号时延估计值,由于参数固定,模型对大气层变化的敏感度十分低,存在估计精度不够高,鲁棒性差等问题。针对经验模型无法对估计参数实时调整的缺点,提出了一种基于经验模型与数字高程的卫星导航信号与定位目标信号自适应时延估计方法。在经验模型估计量的基础上对数字高程值进行估计,并构建自适应卡尔曼滤波器形成误差反馈环,通过迭代计算自适应修正经验模型参数。仿真结果表明,改进的信号时延估计方法能更好地跟踪大气层参数变化,估计误差优于常规经验模型估计结果,有效地提高了卫星导航信号与定位目标信号的定位性能。
The propagation delay of the satellite navigation signal and the positioning target signal in the ionosphere and troposphere is an important error source for the positioning of the Global Navigation Satellite System(GNSS). Estimating the propagation delay of such signals is an important means to improve the system's positioning accuracy. The conventional time-delay estimation method estimates the signal delay estimation based on experience models such as Hopefield and Saastamoinen models. Due to the fixed parameters, the sensitivity of the model to atmospheric changes is very low, so the estimation accuracy is not high enough and the robustness is poor. Aiming at the shortcoming that the empirical model can not adjust the estimation parameters in real time, this paper proposes an adaptive time delay estimation method for satellite navigation signals and positioning target signals based on empirical models and the digital elevation. Based on the estimation of the empirical model, the digital elevation was estimated, and an adaptive Kalman filter is constructed to form an error feedback loop. The parameters of the empirical model was adaptively modified through iterative calculation. The simulation results show that the improved signal delay estimation method can track the variation of atmospheric parameters well, and the estimation error is better than the conventional model estimation results, which can effectively improve the positioning performance of satellite navigation signals and positioning target signals.
The propagation delay of the satellite navigation signal and the positioning target signal in the ionosphere and troposphere is an important error source for the positioning of the Global Navigation Satellite System(GNSS). Estimating the propagation delay of such signals is an important means to improve the system's positioning accuracy. The conventional time-delay estimation method estimates the signal delay estimation based on experience models such as Hopefield and Saastamoinen models. Due to the fixed parameters, the sensitivity of the model to atmospheric changes is very low, so the estimation accuracy is not high enough and the robustness is poor. Aiming at the shortcoming that the empirical model can not adjust the estimation parameters in real time, this paper proposes an adaptive time delay estimation method for satellite navigation signals and positioning target signals based on empirical models and the digital elevation. Based on the estimation of the empirical model, the digital elevation was estimated, and an adaptive Kalman filter is constructed to form an error feedback loop. The parameters of the empirical model was adaptively modified through iterative calculation. The simulation results show that the improved signal delay estimation method can track the variation of atmospheric parameters well, and the estimation error is better than the conventional model estimation results, which can effectively improve the positioning performance of satellite navigation signals and positioning target signals.
引文
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[12] André Hauschild,Oliver Montenbruck,Jean-Marie Sleewaegen,Lennard Huisman,J G Peter.Teunissen.Characterization of Compass M-1 signals[J].GPS Solutions,2012 ,16(1):117-126.
[2] 吴文溢,陈西宏,刘少伟.低仰角对流层散射斜延迟实时估计方法[J/OL].电子与信息学报,2017,39(6):1326-1332.
[3] 汤中山,吴良才.三种对流层延迟模型的精度对比[J].测绘科学,2017,42(2):11-13,17.
[4] 饶爱水,李清梅,胡健,吴关鹏.箭载GPS定位临近地面卫星对流层延迟改正模型[J].中国惯性技术学报,2015,23(5):670-673.
[5] 杨玲,李博峰,楼立志.不同对流层模型对GPS定位结果的影响[J].测绘通报,2009,(4):9-11+64.
[6] Li Wei,Yuan YunBin,Ou JiKun,Li Hui,Li ZiShen.A new global zenith tropospheric delay model IGGtrop for GNSS applications[J].Chinese Science Bulletin,2012,57(17):2132-2139.
[7] 施昆,张能武,字成波.GPS电离层改正模型的评价[J].昆明理工大学学报(理工版),2004,(4):73-78.
[8] 周敏,刘健,杨林,王宇龙,桑青松.一种自适应卡尔曼滤波在动态导航定位中的应用[J].自动化仪表,2016,37(8):1-4.
[9] Oliver Montenbruck,André Hauschild,Peter Steigenberger,Urs Hugentobler,Peter Teunissen,Shinichi Nakamura.Initial assessment of the COMPASS/BeiDou-2 regional navigation satellite system[J].GPS Solutions,2013,17(2):211-222.
[10] 潘林.基于北斗/GPS的微小区域高精度大气时空建模[D].西南交通大学,2016.
[11] 王新龙,李亚峰.GPS定位中4种对流层延迟修正模型适应性分析[J].电光与控制,2008,(11):5-9,18.
[12] André Hauschild,Oliver Montenbruck,Jean-Marie Sleewaegen,Lennard Huisman,J G Peter.Teunissen.Characterization of Compass M-1 signals[J].GPS Solutions,2012 ,16(1):117-126.