  We present both offline and online maximum likelihood estimation (MLE)
techniques for inferring the static parameters of a multiple target tracking
(MTT) model with linear Gaussian dynamics. We present the batch and online
versions of the expectation-maximisation (EM) algorithm for short and long data
sets respectively, and we show how Monte Carlo approximations of these methods
can be implemented. Performance is assessed in numerical examples using
simulated data for various scenarios and a comparison with a Bayesian
estimation procedure is also provided.
