The invention discloses a multi-sensor fusion intelligent brake shoe positioning system based on factor graph elimination optimization, in order to effectively improve the fusion positioning immunity and fault-tolerant capability of the system, a sliding window is added in a navigation system represented by a chain factor graph and is used for reserving a historical state in the window and updating a new state. For rapid amplification of calculation matrix dimensions caused by reservation of a large amount of historical information, an elimination algorithm based on House holder partial QR decomposition is introduced, elimination is sequentially carried out from an old moment state to a new moment state, a chain factor graph is converted into a Bayesian network, and meanwhile, the states after elimination are marginalized, so that when the historical information is reserved, the calculation matrix dimensions are rapidly amplified, and the calculation matrix dimensions are rapidly amplified. And calculation of a large matrix is avoided. And finally, carrying out repeated iteration on the factor graph after elimination by adopting a Gaussian-Newton iteration method to obtain optimal state estimation of fusion positioning.
本发明公开了一种基于因子图消元优化的多传感器融合智能铁鞋定位系统,为了有效提高系统融合定位抗扰性和容错能力,在以链式因子图表示的导航系统中加入一个滑动窗口,用于保留窗口内的历史状态,并对新的状态进行更新。而对于保留大量历史信息引起的计算矩阵维数的急速扩增,引入一种基于Householder部分QR分解的消元算法,对从旧时刻的状态到新时刻的状态依次进行消元,将链式因子图转化为贝叶斯网络,同时边缘化消元后的状态,使其在保留历史信息的同时,避免了对大矩阵的计算。最后,对消元之后的因子图,采用高斯‑牛顿迭代方法反复迭代,获得融合定位的最佳状态估计。
Multi-sensor fusion intelligent iron shoe positioning system and algorithm based on factor graph elimination optimization
一种基于因子图消元优化的多传感器融合智能铁鞋定位系统和算法
2023-05-12
Patent
Elektronische Ressource
Chinesisch
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