Extended emitter target tracking using GM-PHD filter.
If equipped with several radar emitters, a target will produce more than one measurement per time step and is denoted as an extended target. However, due to the requirement of all possible measurement set partitions, the exact probability hypothesis density filter for extended target tracking is com...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2014-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC4260874?pdf=render |
id |
doaj-24f882c7dd924564bdab38999bd46138 |
---|---|
record_format |
Article |
spelling |
doaj-24f882c7dd924564bdab38999bd461382020-11-25T02:13:55ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-01912e11431710.1371/journal.pone.0114317Extended emitter target tracking using GM-PHD filter.Youqing ZhuShilin ZhouGui GaoHuanxin ZouLin LeiIf equipped with several radar emitters, a target will produce more than one measurement per time step and is denoted as an extended target. However, due to the requirement of all possible measurement set partitions, the exact probability hypothesis density filter for extended target tracking is computationally intractable. To reduce the computational burden, a fast partitioning algorithm based on hierarchy clustering is proposed in this paper. It combines the two most similar cells to obtain new partitions step by step. The pseudo-likelihoods in the Gaussian-mixture probability hypothesis density filter can then be computed iteratively. Furthermore, considering the additional measurement information from the emitter target, the signal feature is also used in partitioning the measurement set to improve the tracking performance. The simulation results show that the proposed method can perform better with lower computational complexity in scenarios with different clutter densities.http://europepmc.org/articles/PMC4260874?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Youqing Zhu Shilin Zhou Gui Gao Huanxin Zou Lin Lei |
spellingShingle |
Youqing Zhu Shilin Zhou Gui Gao Huanxin Zou Lin Lei Extended emitter target tracking using GM-PHD filter. PLoS ONE |
author_facet |
Youqing Zhu Shilin Zhou Gui Gao Huanxin Zou Lin Lei |
author_sort |
Youqing Zhu |
title |
Extended emitter target tracking using GM-PHD filter. |
title_short |
Extended emitter target tracking using GM-PHD filter. |
title_full |
Extended emitter target tracking using GM-PHD filter. |
title_fullStr |
Extended emitter target tracking using GM-PHD filter. |
title_full_unstemmed |
Extended emitter target tracking using GM-PHD filter. |
title_sort |
extended emitter target tracking using gm-phd filter. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2014-01-01 |
description |
If equipped with several radar emitters, a target will produce more than one measurement per time step and is denoted as an extended target. However, due to the requirement of all possible measurement set partitions, the exact probability hypothesis density filter for extended target tracking is computationally intractable. To reduce the computational burden, a fast partitioning algorithm based on hierarchy clustering is proposed in this paper. It combines the two most similar cells to obtain new partitions step by step. The pseudo-likelihoods in the Gaussian-mixture probability hypothesis density filter can then be computed iteratively. Furthermore, considering the additional measurement information from the emitter target, the signal feature is also used in partitioning the measurement set to improve the tracking performance. The simulation results show that the proposed method can perform better with lower computational complexity in scenarios with different clutter densities. |
url |
http://europepmc.org/articles/PMC4260874?pdf=render |
work_keys_str_mv |
AT youqingzhu extendedemittertargettrackingusinggmphdfilter AT shilinzhou extendedemittertargettrackingusinggmphdfilter AT guigao extendedemittertargettrackingusinggmphdfilter AT huanxinzou extendedemittertargettrackingusinggmphdfilter AT linlei extendedemittertargettrackingusinggmphdfilter |
_version_ |
1724903260487155712 |