Parameter integration filter and parameter decomposition filter for Autonomous Navigation of BDS
Parameter integration filter and parameter decomposition filter for Autonomous Navigation of BDS
复制标题
北斗自主导航参数积分滤波器和参数分解滤波器
DOI：
10.1007/s10291-017-0640-7
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发表时间：
2017
期刊：
影响因子：
4.9
通讯作者：
龚晓颖
中科院分区：
文献类型：
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作者：
龚晓颖
基于星间交叉链路的自主导航（AutoNav）可以在战争中保持BDS的生存能力，并减轻对作战控制段的需求。它在落实工商发展服务的全球能力方面发挥着重要作用。AutoNav中使用两种滤波器，即参数积分滤波器（PIF）和参数分解滤波器（PDF）。为了讨论哪种滤波器更适合AutoNav，我们比较了PIF和PDF的观测方程，并分析了两种滤波器实现AutoNav的性能。详细地，首先，我们比较了单向观测方程的PIF和双向组合观测方程的PDF的冗余观测，计算成本和观测误差的数量。然后，通过对北斗星座的仿真，分别采用PIF和PDF实现了AutoNav，并从精度、计算效率和参数相关性等方面分析了这两种滤波器的性能。结果表明，PIF和PDF可以达到相当的精度，但PDF的求解时间不到PIF的一半。
Autonomous Navigation (AutoNav) based on inter-satellite cross-link can substantially maintain BDS survivability in war and alleviate the need of the Operational Control Segment. It plays a major role in the implementation of the global capabilities of BDS. There are two kinds of filters used in AutoNav, namely the parameter integration filter (PIF) and the parameter decomposition filter (PDF). In order to discuss which filter is better suitable for AutoNav, we compare observation equations of the PIF and PDF and analyze the performance of AutoNav implemented by the two filters. In detail, first, we compare the one-way observation equation of the PIF and the two-way combined observation equations of the PDF regarding number of redundant observations, computational cost and observation errors. Then, with the simulation of the BDS constellation, we implement AutoNav by the PIF and PDF and analyze the performances of the two filters regarding precision, computational efficiency and parameter correlation. The results show that the PIF and PDF can achieve equivalent precision, but the solution time of the PDF is less than half of that of the PIF.