基于有限元的二维导航随机微分模型求解

Yuxin Zhao, Lijuan Chen, Wenjian Liu
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引用次数: 0

摘要

本文提出了一种应用有限元近似导航系统状态概率密度函数的新方法。导航随机微分模型的弱解用Kolmogorov正演方程表示,求解难度很大。通过有限元求解得到状态的先验概率密度函数,再通过贝叶斯公式得到状态的后验概率密度函数,并以水下航行器组合导航系统为例,与Particle Filter进行对比分析,通过仿真实验结果验证了有限元求解导航随机微分模型的可行性。
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Solving 2-dimensional navigation stochastic differential model based on finite element
A new method applying finite element is proposed in this paper to approximate probability density function of the state of a navigation system. The weak solution of navigation stochastic differential model is denoted by the Kolmogorov's forward equation, which it is very difficult to be obtained. The solution is approached through finite element to obtain a prior probability density function of the state, then a posterior probability density function is gained through Bayesian formula, By taking the underwater vehicle integrated navigation system as the instance and carrying out the contrastive analysis with Particle Filter, the feasibility of solving of navigation stochastic differential model with the help of finite element is confirmed through simulating experiment results.
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