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 language | English |
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Title of host publication | 2018 UKACC 12th International Conference on Control, CONTROL 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 107-112 |
Number of pages | 6 |
ISBN (Electronic) | 9781538628645 |
DOIs | |
Publication status | Published - 31 Oct 2018 |
Event | UKACC 12th International Conference on Control, CONTROL 2018 - Sheffield, United Kingdom Duration: 5 Sept 2018 → 7 Sept 2018 |
Publication series
Name | 2018 UKACC 12th International Conference on Control, CONTROL 2018 |
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Conference
Conference | UKACC 12th International Conference on Control, CONTROL 2018 |
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Country/Territory | United Kingdom |
City | Sheffield |
Period | 5/09/18 → 7/09/18 |
Bibliographical note
Funding Information:This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Grant number EP/K014307/1 and the MOD University Defence Research Collaboration in Signal Processing.
Publisher Copyright:
© 2018 IEEE.
Keywords
- Atmospheric dispersion model
- Bayesian estimation
- Sensor networks
- Source-term estimation