On the uniform asymptotic convergence of a distributed particle filter
On the uniform asymptotic convergence of a distributed particle filter
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分布式粒子滤波器的一致渐近收敛性
DOI：
10.1109/sam.2014.6882385
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
J. Míguez
中科院分区：
文献类型：
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作者：
J. Míguez
在过去的几年中，分布式信号处理算法，适合其实施的无线传感器网络（WSNs）和ad hoc网络的通信和计算能力，已成为一个热门话题。受到特别关注的一类算法是粒子滤波器。然而，这种类型的方法的大多数分布式版本涉及各种启发式或简化近似，因此，标准粒子滤波器的经典收敛定理不适用于它们的分布式对应物。在本文中，我们研究了一个分布式粒子滤波方案，已提出在并行计算系统和无线传感器网络的实施，并证明，在一定的稳定性假设下，有关的物理系统的利益，其渐近收敛是有保证的。此外，我们表明，收敛一致达到随着时间的推移。这意味着近似误差可以在任意长的时间段内保持有界，而不必逐渐增加计算量。
Distributed signal processing algorithms suitable for their implementation over wireless sensor networks (WSNs) and ad hoc networks with communications and computing capabilities have become a hot topic during the past years. One class of algorithms that have received special attention are particles filters. However, most distributed versions of this type of methods involve various heuristic or simplifying approximations and, as a consequence, classical convergence theorems for standard particle filters do not hold for their distributed counterparts. In this paper, we look into a distributed particle filter scheme that has been proposed for implementation in both parallel computing systems and WSNs, and prove that, under certain stability assumptions regarding the physical system of interest, its asymptotic convergence is guaranteed. Moreover, we show that convergence is attained uniformly over time. This means that approximation errors can be kept bounded for an arbitrarily long period of time without having to progressively increase the computational effort.
DOI：
10.3150/14-bej666
发表时间：
2013-09
期刊：
arXiv: Computation
影响因子：
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作者：
N. Whiteley;Anthony Lee;K. Heine
通讯作者：
N. Whiteley;Anthony Lee;K. Heine