Local tracking in clutter initialises and updates true and false tracks. Local false track discrimination uses a track quality measure to confirm most of the true tracks, and to terminate most of the false tracks. Confirmed tracks are transmitted for track-totrack fusion. The sets of tracks being considered for fusion may contain both true and false tracks. The authors assume that each track information also includes the track quality measure in the form of the probability of target existence information. This information is used for additional false track discrimination at the fusion centre. They also use this information to enhance the track-to-track association. They propose three different strategies for track fusion with the target existence information: the 'single target', the 'joint multitarget' and the 'linear multitarget'.

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In a surveillance situation, the origin of each measurement is uncertain. Each measurement may be a clutter measurement or a target detection. In addition to the position [range and angle(s)], measurements often include Doppler velocity. The Doppler velocity measurements are often (e.g. with the linearly modulated frequency transmitted signal) correlated with the range measurements. This study deals with data association (via measurement likelihoods) and estimation in this situation, with a special consideration of the Gaussian mixture approaches. A simulation study shows the benefit of this approach.