BLUE filter with fused range estimation

The non-linear filter is subject to divergence for close-range target tracking; an adaptive best linear unbiased estimation (BLUE) filter with fused range estimation is presented. After proposing the notion of predicted range, the weighted estimation of the predicted and measured ranges is used in t...

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Published inJournal of engineering (Stevenage, England) Vol. 2019; no. 21; pp. 8071 - 8075
Main Authors Hu, Sheng, Wen-bo, Zhao, Si-yuan, Tang
Format Journal Article
LanguageEnglish
Published The Institution of Engineering and Technology 01.11.2019
Wiley
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ISSN2051-3305
2051-3305
DOI10.1049/joe.2019.0685

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Abstract The non-linear filter is subject to divergence for close-range target tracking; an adaptive best linear unbiased estimation (BLUE) filter with fused range estimation is presented. After proposing the notion of predicted range, the weighted estimation of the predicted and measured ranges is used in the converted measurement model to track the target. The adaptive BLUE filtering parameters with Rayleigh range measurement are derived. Simulation results show the adaptive BLUE filter exhibits better robustness and accuracy with modest computational burden.
AbstractList The non-linear filter is subject to divergence for close-range target tracking; an adaptive best linear unbiased estimation (BLUE) filter with fused range estimation is presented. After proposing the notion of predicted range, the weighted estimation of the predicted and measured ranges is used in the converted measurement model to track the target. The adaptive BLUE filtering parameters with Rayleigh range measurement are derived. Simulation results show the adaptive BLUE filter exhibits better robustness and accuracy with modest computational burden.
Author Hu, Sheng
Si-yuan, Tang
Wen-bo, Zhao
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Cites_doi 10.1109/78.978374
10.1109/ACC.2002.1023128
10.1109/CDC.2012.6426622
10.1109/RADAR.2010.5494637
10.1109/ICIF.2007.4408006
10.1109/RADAR.2012.6212236
10.1109/MFI.2006.265588
10.1109/TAC.2009.2019800
10.1109/SSST.2010.5442834
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Issue 21
Keywords fused range estimation
converted measurement model
nonlinear filter
filtering theory
predicted range
target tracking
close-range target tracking
Rayleigh range measurement
adaptive BLUE filter
adaptive best linear unbiased estimation filter
weighted estimation
predicted measured ranges
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Snippet The non-linear filter is subject to divergence for close-range target tracking; an adaptive best linear unbiased estimation (BLUE) filter with fused range...
The non‐linear filter is subject to divergence for close‐range target tracking; an adaptive best linear unbiased estimation (BLUE) filter with fused range...
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SubjectTerms adaptive best linear unbiased estimation filter
adaptive BLUE filter
close-range target tracking
converted measurement model
filtering theory
fused range estimation
IET International Radar Conference (IRC 2018)
nonlinear filter
predicted measured ranges
predicted range
Rayleigh range measurement
target tracking
weighted estimation
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Title BLUE filter with fused range estimation
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