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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 onlineversions of the expectation-maximisation (EM) algorithm for short and long datasets respectively, and we show how Monte Carlo approximations of these methodscan be implemented. Performance is assessed in numerical examples usingsimulated data for various scenarios and a comparison with a Bayesianestimation procedure is also provided.

Estimating the Static Parameters in Linear Gaussian Multiple Target Tracking Models