Integrated IMU and radiolocation-based navigation using a Rao-Blackwellized particle filter
Integrated IMU and radiolocation-based navigation using a Rao-Blackwellized particle filter
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DOI：
10.1109/icassp.2013.6638647
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发表时间：
2013-05
期刊：
影响因子：
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通讯作者：
W. W. Li-W.;R. Iltis;M. Win
中科院分区：
文献类型：
--
作者：
W. W. Li-W.;R. Iltis;M. Win
在本文中，我们开发了一个基于IMU/无线电位置的协作导航系统，其中每个节点不仅根据自己的测量来跟踪位置，而且还通过与邻居节点的协作来跟踪位置。关键问题是设计一种非线性滤波器来融合IMU和无线电定位信息。我们应用Rao-Blackwell化方法，分别使用粒子滤波和并行卡尔曼滤波来估计方位和其他状态(即位置、速度等)。在仿真实验中，该方法的性能明显优于扩展卡尔曼滤波(EKF)。
In this paper, we develop a cooperative IMU/radio-location-based navigation system, where each node tracks the location not only based on its own measurements, but also via collaboration with neighbor nodes. The key problem is to design a nonlinear filter to fuse IMU and radiolocation information. We apply the Rao-Blackwellization method by using a particle filter and parallel Kalman filters for the estimation of orientation and other states (i.e., position, velocity, etc.), respectively. The proposed method significantly outperforms the extended Kalman filter (EKF) in the set of simulations here.