The generalized intensity filter

The task of tracking targets, that generate more than one measurement per scan appears in several applications such as extended object and group tracking. In this case the target (or group) extent implies that multiple measurements, drawn according to a spatial probability distribution, are measured per sensor scan. However, applications exist where targets generate several measurements per sensor scan, which are not geometrically correlated according to a distribution in the measurement space. An example for such an application is Blind Mobile Localization, which is the passive non-cooperative localization and tracking of mobile terminals in urban scenarios. In this paper an Intensity filter for a general scatterer measurement process is presented to track targets with multiple measurements per scan. In this case, the measurements do not necessarily have to be spatially related in the measurement space. Furthermore, a generalization of the probability of detection is discussed. Finally, sequential Monte Carlo implementations of the generalized Intensity and the general Probability Hypothesis filter are used for a numerical evaluation