http://iet.metastore.ingenta.com
1887

Efficient bias reduction approach of time-of-flight-based wireless localisation networks in NLOS states

Efficient bias reduction approach of time-of-flight-based wireless localisation networks in NLOS states

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Radar, Sonar & Navigation — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

An efficient bias mitigation algorithm based on time of flight is proposed for positioning the target location and reducing the non-line-of-sight (NLOS) error and clock jitter error in three-dimensional wireless cooperative localisation networks. Through linearising the range-based expressions and utilising novel three-step weighted linear least squares algorithm, an algebraic solution of target can be derived, in which the clock jitter error and NLOS error can be alleviated effectively. Meanwhile, the Cramer–Rao lower bound (CRLB) is derived for the standard of performance evaluation. The location accuracy of the proposed algorithm is analysed and compared with the conventional methods through simulation experiment. The simulation results indicate that the precision of the proposed algorithm can approach the CRLB, what is more, the proposed algorithm can provide obvious improvements in positioning accuracy compared to the state-of-the-art approaches.

http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rsn.2018.5167
Loading

Related content

content/journals/10.1049/iet-rsn.2018.5167
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address