Resampling algorithms and architectures for distributed particle filters
Resampling algorithms and architectures for distributed particle filters
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DOI：
10.1109/tsp.2005.849185
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发表时间：
2005-07-01
影响因子：
5.4
通讯作者：
Hong, SJ
中科院分区：
文献类型：
--
作者：
Bolic, M;Djuric, PM;Hong, SJ
在本文中，我们提出了新的resception算法的架构，有效的分布式实现的粒子滤波器。所提出的算法提高了可扩展性的过滤器架构的影响，重新排序过程。粒子滤波器实现中的问题，由于resception的描述，并提出了适当的修改resception算法，使分布式实现的开发和研究。研究了粒子按比例分配（RPA）和非比例分配（RNA）的分布式搜索算法.滤波器架构的组件是处理元件（PE）、中央单元（CU）和互连网络。新的恢复算法的主要优点之一是减少了通过互连网络的通信，并使其具有确定性，从而简化了网络结构并提高了采样频率。粒子滤波性能估计的纯方位跟踪应用。在分析的架构部分，粒子滤波器实现的面积和速度估计为不同数量的粒子和不同水平的并行与现场可编程门阵列（FPGA）实现。本文只考虑了采样重要性恢复（SIR）粒子滤波器，但分析可以扩展到任何恢复的粒子滤波器。
In this paper, we propose novel resampling algorithms with architectures for efficient distributed implementation of particle filters. The proposed algorithms improve the scalability of the filter architectures affected by the resampling process. Problems in the particle filter implementation due to resampling are described, and appropriate modifications of the resampling algorithms are proposed so that distributed implementations are developed and studied. Distributed resampling algorithms with proportional allocation (RPA) and nonproportional allocation (RNA) of particles are considered. The components of the filter architectures are the processing elements (PEs), a central unit (CU), and an interconnection network. One of the main advantages of the new resampling algorithms is that communication through the interconnection network is reduced and made deterministic, Which results in simpler network structure and increased sampling frequency. Particle filter performances are estimated for the bearings-only tracking applications. In the architectural part of the analysis, the area and speed of the particle filter implementation are estimated for a different number of particles and a different level of parallelism with field programmable gate array (FPGA) implementation. In this paper, only sampling importance resampling (SIR) particle filters are considered, but the analysis can be extended to any particle filters with resampling.