Open AccessDistributed path optimisation of mobile sensor networks for AOA target localisation
Author(s) -
Yang Ziwen,
Zhu Shanying,
Chen Cailian,
Guan Xinping,
Feng Gang
Publication year - 2019
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.2018.6112
Subject(s) - wireless sensor network , path (computing) , computer science , gradient descent , control theory (sociology) , angle of arrival , real time computing , trajectory , filter (signal processing) , function (biology) , mathematical optimization , mathematics , artificial intelligence , artificial neural network , computer vision , computer network , telecommunications , physics , control (management) , astronomy , evolutionary biology , antenna (radio) , biology
The path optimisation problem of mobile sensor networks for arrival‐of‐angle (AOA) target localisation, using the consensus‐based extended information filter is considered, in this study. A new idea of equipping sensors with information‐driven mobility to improve the estimation accuracy with respect to a stationary target is proposed by the authors. A gradient descent method is used for mobile sensors, which are subject to geometric constraints, to choose the next optimal waypoints. The corresponding optimisation problem is solved in a distributed manner, by selecting a proper cost function for each mobile sensor. It is shown that the boundedness of the estimation error is guaranteed. Moreover, they find that the mobility of sensors does decrease the estimation error bounds compared with the static sensor networks, which is beneficial for the localisation performance. Simulation is carried out to show the effectiveness of the proposed method.