Measurement variance ignorant target motion analysis

Ristic, B, Arulampalam, S and Wang, X 2018, 'Measurement variance ignorant target motion analysis', Information Fusion, vol. 43, pp. 27-32.

Document type: Journal Article
Collection: Journal Articles

Title Measurement variance ignorant target motion analysis
Author(s) Ristic, B
Arulampalam, S
Wang, X
Year 2018
Journal name Information Fusion
Volume number 43
Start page 27
End page 32
Total pages 6
Publisher Elsevier
Abstract The paper is devoted to Bayesian target motion analysis (TMA) for the case when the variance of additive white zero-mean Gaussian measurement noise is unknown. Two Rao-Blackwellised particle filters for TMA are developed, which jointly estimate the target state and the measurement variance. The error performance of the two particle filters is compared against the theoretical Cramer-Rao lower bound. The bound suggests the error in target state estimation is not affected by the ignorance of the measurement noise variance. Both developed TMA algorithms reach this theoretical bound, however, one is significantly faster.
Subject Signal Processing
Keyword(s) Target motion analysis
bearings-only tracking
noise adaptive nonlinear filtering
Particle filter
DOI - identifier 10.1016/j.inffus.2017.11.006
Copyright notice Crown Copyright © 2017 Published by Elsevier B.V. All rights reserved.
ISSN 1566-2535
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Citation counts: TR Web of Science Citation Count  Cited 1 times in Thomson Reuters Web of Science Article | Citations
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