An Advanced Auxiliary Delay-Weight Particle Filter with Linear Computation Cost

We investigate the problem of tracking mobile targets in wireless sensor networks. We propose an advanced auxiliary delayed-weight particle filter algorithm (ADWPF). We make a deep study on the evolvement of particles and formally define the tree-like structure relationship among particles based on...

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Main Authors: Chen Li, Lin Sun, Zengwei Zheng, Dan Chen
Format: Article
Language:English
Published: Wiley 2016-05-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2016/4535963
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author Chen Li
Lin Sun
Zengwei Zheng
Dan Chen
author_facet Chen Li
Lin Sun
Zengwei Zheng
Dan Chen
author_sort Chen Li
collection DOAJ
description We investigate the problem of tracking mobile targets in wireless sensor networks. We propose an advanced auxiliary delayed-weight particle filter algorithm (ADWPF). We make a deep study on the evolvement of particles and formally define the tree-like structure relationship among particles based on observations. Most importantly, we add some auxiliary particles to these structures formed by sampled particles in order to obtain more efficient structures. Based on the newly tree-like structures formed by auxiliary particles and sampled particles, we design a well efficient delayed-weight algorithm with linear computation cost. Experiment results demonstrate that our algorithm can greatly improve the tracking accuracy of a mobile target, compared with bootstrap filter, auxiliary particle filter, and another delayed-weight particle filter.
format Article
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institution Kabale University
issn 1550-1477
language English
publishDate 2016-05-01
publisher Wiley
record_format Article
series International Journal of Distributed Sensor Networks
spelling doaj-art-99651d3d922148e4b2ca028d7a794d002025-08-20T03:37:03ZengWileyInternational Journal of Distributed Sensor Networks1550-14772016-05-011210.1155/2016/4535963An Advanced Auxiliary Delay-Weight Particle Filter with Linear Computation CostChen Li0Lin Sun1Zengwei Zheng2Dan Chen3 College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China Hangzhou Key Laboratory for IoT Technology & Application, Zhejiang University City College, Hangzhou 310015, China Hangzhou Key Laboratory for IoT Technology & Application, Zhejiang University City College, Hangzhou 310015, China Hangzhou Key Laboratory for IoT Technology & Application, Zhejiang University City College, Hangzhou 310015, ChinaWe investigate the problem of tracking mobile targets in wireless sensor networks. We propose an advanced auxiliary delayed-weight particle filter algorithm (ADWPF). We make a deep study on the evolvement of particles and formally define the tree-like structure relationship among particles based on observations. Most importantly, we add some auxiliary particles to these structures formed by sampled particles in order to obtain more efficient structures. Based on the newly tree-like structures formed by auxiliary particles and sampled particles, we design a well efficient delayed-weight algorithm with linear computation cost. Experiment results demonstrate that our algorithm can greatly improve the tracking accuracy of a mobile target, compared with bootstrap filter, auxiliary particle filter, and another delayed-weight particle filter.https://doi.org/10.1155/2016/4535963
spellingShingle Chen Li
Lin Sun
Zengwei Zheng
Dan Chen
An Advanced Auxiliary Delay-Weight Particle Filter with Linear Computation Cost
International Journal of Distributed Sensor Networks
title An Advanced Auxiliary Delay-Weight Particle Filter with Linear Computation Cost
title_full An Advanced Auxiliary Delay-Weight Particle Filter with Linear Computation Cost
title_fullStr An Advanced Auxiliary Delay-Weight Particle Filter with Linear Computation Cost
title_full_unstemmed An Advanced Auxiliary Delay-Weight Particle Filter with Linear Computation Cost
title_short An Advanced Auxiliary Delay-Weight Particle Filter with Linear Computation Cost
title_sort advanced auxiliary delay weight particle filter with linear computation cost
url https://doi.org/10.1155/2016/4535963
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