Performance of distributed sensing algorithms with correlated noise and defective sensors

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Correlated noise is studied in the context of distributed sensing problems. Previous work has examined the problem of performing distributed estimation in the presence of sensor defects. These defects disrupt sensor measurements but allow the other subsystems of the sensor node to operate normally. Provably optimal and fully distributed estimation algorithms exist for this scenario. A series of computer simulation experiments was conducted to measure how these estimation algorithms are affected by the presence of correlations between various random quantities in the problem setup. Numerical results demonstrate that, in particular network configurations, correlations between sensor defects and communication links can practically alter the performance of distributed estimation algorithms.

Original languageEnglish
Title of host publicationProceedings of 2017 2nd International Conference on Communication and Information Systems, ICCIS 2017
PublisherAssociation for Computing Machinery
Pages126-130
Number of pages5
ISBN (Electronic)9781450353489
DOIs
Publication statusPublished - Nov 7 2017
Event2nd International Conference on Communication and Information Systems, ICCIS 2017 - Wuhan, China
Duration: Nov 7 2017Nov 9 2017

Conference

Conference2nd International Conference on Communication and Information Systems, ICCIS 2017
CountryChina
CityWuhan
Period11/7/1711/9/17

Keywords

  • Sensor networks; distributed sensing

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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