Reliable Sensor Location for Object Positioning and Surveillance via Trilateration

Kun An, Siyang Xie, Yanfeng Ouyang

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

6 Citations (Scopus)


Object positioning and surveillance has been playing an important role in various indoor location-aware applications. Signal attenuation or blockage often requires multiple local sensors to be used jointly to provide coverage and determine object locations via mobile devices. The deployment of sensors has a significant impact on the accuracy of positioning and effectiveness of surveillance. In this paper, we develop a reliable sensor location model that aims at optimizing the location of sensors so as to maximize the accuracy of object positioning/surveillance under the risk of possible sensor disruptions. We formulate the problem as a mixed-integer linear program and develop solution approaches based on a customized Lagrangian relaxation algorithm with an embedded approximation subroutine. A series of hypothetical examples and a real-world Wi-Fi access point design problem for Chicago O'Hare Airport Terminal 5 are used to demonstrate the applicability of the model and solution algorithms. Managerial insights are also presented.

Original languageEnglish
Title of host publicationTransportation Research Procedia
Number of pages18
Publication statusPublished - 2017
EventInternational Symposium on Transportation and Traffic Theory 2017 - Chicago, United States of America
Duration: 24 Jul 201726 Jul 2017
Conference number: 22nd

Publication series

NameTransportation Research Procedia
ISSN (Print)2352-1465


ConferenceInternational Symposium on Transportation and Traffic Theory 2017
Country/TerritoryUnited States of America


  • disruption
  • Lagrangian relaxation
  • sensor location
  • trilateration

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