Scalar estimation from unreliable binary observations

Ryan M. Corey, Andrew Carl Singer

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

Abstract

We consider a scalar signal estimator based on unreliable observations. The proposed architecture forms an estimate using redundant arrays of unreliable binary sensors with detection thresholds that can vary randomly about their nominal values. We analyze the achievable performance of the estimator in terms of mean square error. We also provide approximate expressions for the error of a mean square optimal estimator in terms of the degree of redundancy in the system and the distribution of the random thresholds. We show that calibration and redundancy can compensate for uncertainty in the observations to form a reliable estimate.

Original languageEnglish (US)
Title of host publication2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
PublisherIEEE Computer Society
Pages145-148
Number of pages4
ISBN (Print)9781479914814
DOIs
StatePublished - 2014
Event2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014 - A Coruna, Spain
Duration: Jun 22 2014Jun 25 2014

Publication series

NameProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
ISSN (Electronic)2151-870X

Other

Other2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
Country/TerritorySpain
CityA Coruna
Period6/22/146/25/14

ASJC Scopus subject areas

  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Scalar estimation from unreliable binary observations'. Together they form a unique fingerprint.

Cite this