HMM triangle relative entropy concepts in sequential change detection applied to vision-based dim target manoeuvre detection
Molloy, Timothy & Ford, Jason J. (2012) HMM triangle relative entropy concepts in sequential change detection applied to vision-based dim target manoeuvre detection. In How, Khee Yin (Ed.) Proceedings of the 15th International Conference on Information Fusion, Raffles City Convention Centre, Singapore, pp. 255-262.
The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications.
Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator.
Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.
Impact and interest:
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||hidden Markov model, sequential change detection, manoeuvre detection, dim target tracking, parameter estimation, relative entropy|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)|
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
|Divisions:||Current > Research Centres > Australian Research Centre for Aerospace Automation|
Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||© 2012 ISIF.|
|Deposited On:||06 Jul 2012 09:19|
|Last Modified:||19 Mar 2013 10:51|
Repository Staff Only: item control page