组合导航后验方差异步融合算法

Integrated navigation algorithm with posterior variance and asynchronous fusion

中文关键词  异步融合  后验方差  量测预测值  互不相关性  后验均值

英文关键词  asynchronous fusion  posterior variance  forecast measure value  un-correlation  posterior mean value

中文摘要

      当组合导航系统在工作中对各个导航系统提供的信息进行融合计算时会出现导航数据异步到达的现象, 传统的组合导航异步融合算法在处理这种情况时会产生较为明显的误差. 针对这一问题, 设计基于组合导航后验 方差异步融合算法解决组合导航系统中出现的信息异步融合计算问题. 首先改进系统噪声和量测噪声, 使其在数学 表达上满足互不相关性要求; 然后通过求解后验均值计算出后验方差, 建立状态一步预测值计算方法; 最后基于上 述结果设计组合导航系统的后验方差异步融合算法方程组. 仿真结果表明, 相比传统的组合导航融合算法, 提出的 组合导航后验方差异步融合算法可以有效减少因导航系统信息异步到达而引起的融合计算误差, 有效提高组合导 航系统的导航精度.

英文摘要

      When the integrated navigation system inosculates navigation information that is obtained from every navigation system, the navigation data may arrives at the fusion center asynchronous. The traditional integrated navigation asynchronous fusion algorithm may produce much error when it deals with asynchronous data. Aiming at this problem, the integrated navigation algorithm with posterior variance and asynchronous fusion is designed to solve the asynchronous fusion problem in the system. First of all, system noise and measure noise about the integrated navigation system are improved to make sure they are un-correlated. Then posterior variance is computed through posterior mean value and design the first prediction calculate way about state variable. At last the integrated navigation asynchronous fusion set of equations is set up based on posterior variance and asynchronous fusion algorithm. Simulation shows that the integrated navigation asynchronous fusion algorithm can decrease the error effectively which caused by asynchronous data than traditional integrated navigation asynchronous fusion algorithm and increase the whole integrated navigation system’s precision.