Abstract

A new method of high-precision positioning of mobile objects moving along program trajectories is proposed based on processing of satellite navigation measurements using robust filtering algorithms. The method is based both on the possibility of approximating (in particular, using electronic maps) the program trajectory of an object with a set of trajectory intervals with known analytical dependencies of navigation parameters and on the use of robust stochastic filtering methods that take into account the characteristic dynamics of the object and the uncertain nature of the type of interference distributions of Doppler and code satellite measurements. Electronic map information providing high accuracy of trajectory binding is integrated with algorithms of robust nonlinear filtering of satellite measurements that are optimal by the criterion of minimum nonlinear function of the measurement residual determined by the class of interference distributions of Doppler and code measurements. This makes it possible to significantly reduce computing costs while significantly improving the accuracy of positioning an object. The effectiveness of the proposed method is illustrated by a numerical example.

中文翻译：

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使用卫星导航测量对分析轨迹上的移动物体进行鲁棒定位

摘要

基于使用鲁棒滤波算法处理卫星导航测量结果，提出了一种沿程序轨迹移动的移动物体高精度定位的新方法。该方法基于利用一组具有已知的导航参数分析依赖性的轨迹间隔来近似（特别是使用电子地图）对象的程序轨迹的可能性，以及基于使用鲁棒的随机过滤方法，该方法考虑了物体的特征动态以及多普勒和代码卫星测量的干扰分布类型的不确定性。提供高精度轨迹绑定的电子地图信息与卫星测量的鲁棒非线性滤波算法集成，该算法通过由多普勒和代码测量的干扰分布类别确定的测量残差的最小非线性函数的标准来优化。这使得可以显着降低计算成本，同时显着提高对象定位的精度。通过数值例子说明了该方法的有效性。