Estimation method of false alarm probability and observation noise variance in wireless sensor networks

T. Fujita, T. Ohtsuki, T. Kaneko

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

Abstract

Likelihood Ratio Test (LRT) and Best Linear Unbiased Estimator (BLUE) have been researched as estimation methods of observation event in sensor network. LRT and BLUE can estimate the observation event with high accuracy at the Fusion Center (FC) when the FC has a perfect knowledge of observation statistics of each sensor node. However, all the sensor nodes ' observation statistics are not always available at the FC. In this paper, we propose a method to estimate false alarm probability and observation noise variance of each sensor node at the FC, and present the performance of LRT and BLUE using the proposed estimation method. We show that the LRT and BLUE using the proposed method achieve almost the same bit error rate (BER) as the conventional LRT and BLUE with perfect knowledge of them.

Original languageEnglish
Title of host publication2006 9th International Conference on Information Fusion, FUSION
DOIs
Publication statusPublished - 2006
Event2006 9th International Conference on Information Fusion, FUSION - Florence, Italy
Duration: 2006 Jul 102006 Jul 13

Publication series

Name2006 9th International Conference on Information Fusion, FUSION

Other

Other2006 9th International Conference on Information Fusion, FUSION
Country/TerritoryItaly
CityFlorence
Period06/7/1006/7/13

Keywords

  • BLUE
  • Detection
  • False alarm probability
  • LRT
  • Observation noise variance

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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