Abstract
We consider source localization in a wireless sensor network in the absence of a fusion center, where each sensor makes hybrid time-of-arrival (TOA) and direction-of-arrival (DOA) measurements. Specially, in this paper, we focus on the bounded noise case. Distributed location estimation is posed as a consensus problem. The average consensus method in the literature can be used for a linear fusion estimator which can be written as the ratio of two averages. The disadvantage of this average consensus method is that it can only used for linear model and needs to wait for the final convergence to achieve an acceptable accuracy. However, generally its convergence rate is low. Alternatively, we present a convex projection consensus method where we show that the resulting estimator at each sensor converges to a common point lying in the intersection of convex regions that are determined based on local sensor measurements and also the minimum number of sensors required to meet a certain estimation error tolerance is derived. Numerical results are presented showing the convergence properties and root mean squared error under both the average consensus and the convex projection methods.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.