Bayesian Estimation of A Periodically-Releasing Biochemical Source Using Sensor Networks

Liang Hu, Jinya Su, Michael Hutchinson, Cunjia Liu, Wen Hua Chen

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

Abstract

This paper develops a Bayesian estimation method to estimate source parameters of a biochemical source using a network of sensors. Based on existing models of continuous and instantaneous releases, a model of discrete and periodic releases is proposed, which has extra parameters such as the time interval between two successive releases. Different from existing source term estimation methods, based on the sensor characteristic of chemical sensors, the zero readings of sensors are exploited in our algorithm where the zero readings may be caused by the concentration being below the threshold of the sensors. Two types of Bayesian inference algorithms for key parameters of the sources are developed and their particle filtering implementation is discussed. The efficiency of the proposed algorithms for periodic release is demonstrated and verified by simulation where the algorithm with the exploitation of the zero readings significantly outperforms that without.

Original languageEnglish
Title of host publication2018 UKACC 12th International Conference on Control, CONTROL 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages107-112
Number of pages6
ISBN (Electronic)9781538628645
DOIs
Publication statusPublished - 31 Oct 2018
EventUKACC 12th International Conference on Control, CONTROL 2018 - Sheffield, United Kingdom
Duration: 5 Sep 20187 Sep 2018

Publication series

Name2018 UKACC 12th International Conference on Control, CONTROL 2018

Conference

ConferenceUKACC 12th International Conference on Control, CONTROL 2018
Country/TerritoryUnited Kingdom
CitySheffield
Period5/09/187/09/18

Keywords

  • Atmospheric dispersion model
  • Bayesian estimation
  • Sensor networks
  • Source-term estimation

Fingerprint

Dive into the research topics of 'Bayesian Estimation of A Periodically-Releasing Biochemical Source Using Sensor Networks'. Together they form a unique fingerprint.

Cite this