在给出捷联惯性导航系统动基座大方位失准角误差模型的基础上,推导了粒子滤波方法(Particle Filter,PF),并将扩展卡尔曼滤波、基于Scaled-Unscented变换的Unscented卡尔曼滤波(Uns...
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为提高被动跟踪性能，提出了一种高斯和粒子滤波方法。
To improve the performance of passive tracking, the Gaussian sum particle filter (GSPF) was proposed.
粒子滤波方法由于能够灵活地处理非线性非高斯系统而被广泛地应用。
Particle filter is widely used because of its flexibility to deal with the nonlinear non-Gaussian systems.
其主要内容包括移动机器人的位姿跟踪方法、马尔可夫定位方法、粒子滤波方法及各种粒子滤波改进方法。
The research topics include approaches of robot's pose tracking, Markov localization, Particle Filter and other improved PF method.
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