Sigma-Point Filters: An Overview with Applications to Integrated Navigation and Vision Assisted Control
Sigma-Point Filters: An Overview with Applications to Integrated Navigation and Vision Assisted Control
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西格玛点滤波器：集成导航和视觉辅助控制应用概述
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发表时间：
2006
期刊：
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通讯作者：
E. Wan
中科院分区：
文献类型：
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作者：
E. Wan
在本次报告中，我们首先对西格玛点滤波方法进行综述，其中包括无迹卡尔曼滤波器（UKF）、中心差分卡尔曼滤波器（CDKF）以及几种与顺序蒙特卡罗滤波（例如粒子滤波）混合扩展的变体。在后半部分，我们重点关注其在组合导航系统（INS）中的最新应用，该系统通过结合全球定位系统（GPS）和惯性测量来提供状态估计。此外，我们还介绍了利用视频数据提取等效状态信息（即替代惯性导航系统）以用于无人驾驶飞行器（UAV）闭环控制的新研究成果。
In this presentation, we first provide an overview of Sigma-Point filtering methods, which include the Unscented Kalman Filter (UKF), Central Difference Kalman Filter (CDKF), and several variants with hybrid extensions to sequential Monte Carlo filtering (e.g., particle filtering). In the second half, we focus on recent applications to integrated navigation systems (INS), which provide state-estimation by combining GPS and inertial measurements. In addition, we present new work on using video data to extract the equivalent state-information (i.e., replacing the INS) for use in closed-loop control of an Unmanned Aerial Vehicle (UAV).