2026-09-19T16:59:37Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/120152 2023-09-04 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Kravets, Robin H 2023-05 application/pdf en text Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms The student, Vasista Vovveti, accepted the attached license on 2023-05-01 at 10:38. The student, Vasista Vovveti, submitted this Thesis for approval on 2023-05-01 at 10:41. This Thesis was approved for publication on 2023-05-02 at 11:32. DSpace SAF Submission Ingestion Package generated from Vireo submission #19274 on 2023-09-01 at 16:56:04 Wireless relative localization Vovveti, Vasista 2023-05-02 Localization Wireless Localization Relative Localization Wireless localization performed using least squares absolute trilateration requires collecting data about the environment and is greatly affected by noise. This paper presents a novel approach to wireless localization by relating signal strength measurements from anchors to each other. Relative wireless localization outperforms absolute trilateration in multiple environments with varying amounts of noise. Relative localization does this while removing the requirement for environmental pretraining. Text eng https://hdl.handle.net/2142/120152 © 2023 Vasista Vovveti M.S. Thesis Computer Science University of Illinois at Urbana-Champaign Computer Science