In contrast to situations with well-separated or crossing targets, two phenomena make tracking of closely-spaced objects more difficult: First, the data association problem for multiple targets must be handled over a longer time until the group finally dissolves into well-separated targets. The critical moment of split-off is typically unknown and may even be accompanied with strong maneuvers. Second, due to the finite resolution of every physical sensor, closely-spaced targets might well be unresolvable. With a simplified model of the sensor resolution, possibly unresolved measurements can be treated in combination with the association task. The problems addressed are even more significant in case of dense clutter interference, imperfect target detections, and inaccurate measurements. By taking resolution conflicts explicitly into account, we discuss quantitative results for track maintenance under various conditions within the framework of Bayesian IMM-MHT methods, i.e. tracking of maneuvering formations during spatially or temporarily limited interference. The filter performance is evaluated for typical radar parameters and air situations involving two targets. In particular, the phenomenon of mixing target identities during a formation flight is addressed. The achieved results are compared with more conventional alternatives (MHT, standard JPDAF) that do not consider resolution conflicts.