Method for estimation of gravitational-wave transient model parameters in frequency-time maps

A common technique for detection of gravitational-wave (GW) signals is searching for excess power in frequency-time (ft)-maps of GW detector data. In the event of a detection, model selection and parameter estimation will be performed in order to explore the properties of the source. In this paper, we develop a Bayesian statistical method for extracting model-dependent parameters from observed GW signals in ft-maps. We demonstrate the method by recovering the parameters of model GW signals added to simulated advanced LIGO noise. We also characterize the performance of the method and discuss prospects for future work.