Open AccessRecursive source localisation by time difference of arrival sensor networks with sensor position uncertainty
Author(s) -
Qu Xiaomei,
Xie Lihua
Publication year - 2014
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2014.0245
Subject(s) - position (finance) , control theory (sociology) , computer science , arrival time , wireless sensor network , time of arrival , multilateration , real time computing , artificial intelligence , engineering , acoustics , control (management) , telecommunications , physics , computer network , finance , economics , wireless , transport engineering , node (physics)
In a passive sensor network, time difference of arrival (TDOA) measurements are often exploited for source localisation. The extended Kalman filter (EKF) is usually used for source localisation in a mobile sensor network; however, its performance is limited because of the non‐linearity of the TDOA in relation to the source position. Especially when the available sensor positions include uncertainties, accurate localisation becomes much more challenging. To improve the localisation performance, this study develops two linear recursive three‐dimensional source localisation algorithms by taking into consideration the random sensor position noises. An illustrative example is given to demonstrate that the proposed linear recursive localisation algorithms outperform the EKF localisation algorithm. Performance comparison between the two proposed algorithms is also provided.