One of the primary tasks of wireless sensor networks is to monitor a Field of Interest (FoI). The availability of observations is directly related to the number of sensors able to sense a particular event, and can be quantified by computing the fraction of the FoI covered by at least a threshold number of sensors, also known as k-coverage. Previous work on evaluating the k-coverage assumed that sensors have identical sensing areas and/or conform to the idealized unit disk model. However, we consider sensors of multiple sensing modalities such as acoustic, optical, infrared, CCD, magnetic or thermal, that have sensing areas significantly different than the unit disk model, and that may be concurrently deployed, thus forming a heterogeneous wireless sensor network (WSN). Alternatively, for applications such as area surveillance and habitat monitoring, the network performance is related to how well the deployed network can monitor mobile targets that cross the FoI. We quantify the latter by computing the probability of detecting a target crossing the FoI. As in the case of k-coverage, analytically computing the target detection probability assuming a heterogeneous WSN is a challenging problem.