Geolocation with Graph-Based Model Fitting

Tsvi G. Dvorkind, Yonina C. Eldar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We address the problem of geolocation in a search and rescue mission where a person with a hand-held transmitter is to be located by a sporadic set of receivers, which measure the received power of the transmitted distress beacon. As simple propagation models are insufficient to correctly predict the received powers, we suggest to use the region topology in order to derive a graph-based structure. The latter is then exploited for simultaneous model adjustment and geolocation. Simulations demonstrate the effectiveness of the suggested method.

Original languageEnglish
Title of host publication2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings
Pages356-360
Number of pages5
ISBN (Electronic)9781728155494
DOIs
StatePublished - Dec 2019
Event8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Le Gosier, Guadeloupe
Duration: 15 Dec 201918 Dec 2019

Publication series

Name2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings

Conference

Conference8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019
Country/TerritoryGuadeloupe
CityLe Gosier
Period15/12/1918/12/19

All Science Journal Classification (ASJC) codes

  • Control and Optimization
  • Artificial Intelligence
  • Computer Networks and Communications

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