dc.contributor.authorYang, Rong
dc.contributor.authorFoo, Pek Hui
dc.contributor.authorTan, Peng Yen
dc.contributor.authorSee, Elaine Mei Eng
dc.contributor.authorNg, Gee Wah
dc.contributor.authorNg, Boon Poh
dc.identifier.citationYang, R., Foo, P. H., Tan, P. Y., See, E. M. E., Ng, G. W., & Ng, B. P. (2012). Indoor contaminant source estimation using a multiple model unscented Kalman filter. 2012 15th International Conference on Information Fusion (FUSION), 1854-1859.en_US
dc.description.abstractThe contaminant source estimation problem is getting increasing importance due to more and more occurrences of sick building syndrome and attacks from covert chemical warfare agents. To monitor a building contamination condition, a number of sensors are connected through a network, and the sensor measurements are sent to a fusion center to estimate contaminant source information. An estimation algorithm is required such that timely actions can be taken to mitigate the adverse effects. This paper proposes a multiple model unscented Kalman filter (MM-UKF) to estimate the contaminant source location, the source emission rate and the release time. A simulation test is conducted on a computer generated three-story building. The results show that the MM-UKF algorithm can achieve real-time estimation.en_US
dc.rights© 2012 International Society of Information Fusion. This paper was published in 2012 15th International Conference on Information Fusion (FUSION) and is made available as an electronic reprint (preprint) with permission of International Society of Information Fusion. The paper can be found at the following official URL:http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6290526. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.en_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering
dc.titleIndoor contaminant source estimation using a multiple model unscented Kalman filteren_US
dc.typeConference Paper
dc.contributor.conferenceInternational Conference on Information Fusion (15th : 2012)en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.versionPublished versionen_US

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