Yildirim, S and Jiang, L and Singh, SS and Dean, TA (2014) Calibrating the Gaussian multi-target tracking model. Statistics and Computing. pp. 1-14. ISSN 0960-3174Full text not available from this repository.
We present novel batch and online (sequential) versions of the expectation-maximisation (EM) algorithm for inferring the static parameters of a multiple target tracking (MTT) model. Online EM is of particular interest as it is a more practical method for long data sets since in batch EM, or a full Bayesian approach, a complete browse of the data is required between successive parameter updates. Online EM is also suited to MTT applications that demand real-time processing of the data. Performance is assessed in numerical examples using simulated data for various scenarios. For batch estimation our method significantly outperforms an existing gradient based maximum likelihood technique, which we show to be significantly biased. © 2014 Springer Science+Business Media New York.
|Uncontrolled Keywords:||Expectation-maximization Multiple target tracking Online Parameter estimation Particle filters|
|Divisions:||Div F > Signal Processing and Communications|
|Depositing User:||Unnamed user with email email@example.com|
|Date Deposited:||16 Jul 2015 13:19|
|Last Modified:||26 Jul 2015 00:58|