Abstract
This research presents a distributed and low-complexity algorithm for range-based localization in wireless sensor networks (WSNs), which is an extension of the Distributed Spatially Constrained Local (DSCL) algorithm. The proposed method uses robust functions suitable to avoid outliers derived from corrupted estimated distances among sensor nodes, where the estimated distances are generated under two well known range-estimation techniques. The accuracy of the proposed algorithm was tested using a set of 10 distributed WSNs with noisy distance measurements between sensor nodes, deployed arbitrarily on a 2-D area of 100 m x 100 m. Regarding to the DSCL algorithm, the proposed approach DSCL/Smooth-l_1 reduces, in average, around 57% the error on position estimates under the RSSI model. On the other hand, the scheme DSCL/Cauchy-Lorentzian greatly outperforms the original one in the presence of outliers in distance estimates.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
