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Selectively resampling particle filter

机译:选择性重采样粒子过滤器

摘要

A method, and program for implementing such method, for use in estimating a conditional probability distribution for past signal states, current signal states, future signal states, and/or complete pathspace of a non-linear random dynamic signal process, includes providing sensor measurement data associated therewith and state data including at least location and weight information associated with each of a plurality of particles as a function thereof. An estimate of the conditional probability distribution is compared for the signal state based on the state data for particles under consideration and such particles are resampled upon receipt of sensor measurement data. The resampling includes comparing weight information associated with a first particle (e.g., the highest weighted particle) with weight information associated with a second particle (e.g., the lowest weighted particle) to determine if the state data of the first and second particles is to be adjusted.
机译:用于估计非线性随机动态信号过程的过去信号状态,当前信号状态,未来信号状态和/或完整路径空间的条件概率分布的方法和实现该方法的程序,包括提供传感器测量与之相关的数据和状态数据至少包括与多个颗粒中的每一个相关的位置和重量信息。基于考虑中的粒子的状态数据,针对信号状态比较条件概率分布的估计值,并在接收到传感器测量数据后对此类粒子进行重新采样。重采样包括将与第一粒子(例如,权重最高的粒子)关联的权重信息与与第二粒子(例如,权重最低的粒子)关联的权重信息进行比较,以确定第一和第二粒子的状态数据是否为调整。

著录项

  • 公开/公告号US7058550B2

    专利类型

  • 公开/公告日2006-06-06

    原文格式PDF

  • 申请/专利权人 MICHAEL A. KOURITZIN;

    申请/专利号US20040877879

  • 发明设计人 MICHAEL A. KOURITZIN;

    申请日2004-06-25

  • 分类号G06F15/00;

  • 国家 US

  • 入库时间 2022-08-21 21:41:06

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