李天成
基于受限测距传感网的分布式多目标跟踪
2018-12-14 16:54
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标签:分布式网络, 目标跟踪, 随机集, Diffusion, 一致性, Diffusion, Diffusion

Local-Diffusion-based Distributed SMC-PHD Filtering Using Sensors with Limited Sensing Range

Tiancheng Li Víctor Elvira Hongqi Fan Juan M. Corchado

IEEE Sensors Journal


Abstract:

We investigate the problem of distributed multitarget tracking by using a set of spatially dispersed, collaborative sensors with limited sensing range (LSR), where each sensor runs a sequential Monte Carlo-probability hypothesis density filter and exchanges relevant posterior information with its neighbors. The key challenge stems from the LSR of neighbor sensors whose fields of view (FoVs) are partially/non-overlapped and therefore they may observe different targets at the same time. With regard to the local common FoVs among neighbor sensors, the proposed distributed fusion scheme, called local diffusion, performs one iteration of neighbor communication per filtering step in either of two means. One is given by immediate particle exchange, in which a reject-control operation is devised to reduce the number of communicating particles. The other is done by converting the particle distribution to Gaussian functions for parametric information exchange and fusion. The performance of both approaches has been experimentally investigated via simulation for different LSR situations and compared with cutting-edge approaches.



T. Li, V. Elvira, H. Fan and J. M. Corchado, "Local-Diffusion-Based Distributed SMC-PHD Filtering Using Sensors With Limited Sensing Range," in IEEE Sensors Journal, vol. 19, no. 4, pp. 1580-1589, 15 Feb.15, 2019.
doi: 10.1109/JSEN.2018.2882084


@ARTICLE{Li2019local, 
author={T. Li and V. Elvira and H. Fan and J. M. Corchado}, 
journal={IEEE Sensors Journal}, 
title={Local-Diffusion-Based Distributed \cal{SMC-PHD} Filtering Using Sensors With Limited Sensing Range}, 
year={2019}, 
volume={19}, 
number={4}, 
pages={1580-1589}, 
doi={10.1109/JSEN.2018.2882084}, 
ISSN={1530-437X}, 
month={Feb.},}

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