This paper presents a new coverage formulation addressing the quality of service of sensor networks that cooperatively detect targets traversing a region of interest. The problem of track coverage consists of finding the positions of n sensors such that a Lebesgue measure on the set of tracks detected by at least k sensors is optimized. This paper studies the geometric properties of the network, addressing a deterministic track coverage formulation and binary sensor models. It is shown that the tracks detected by a network of heterogeneous omnidirectional sensors are the geometric transversals of nontranslates families of circles. A novel methodology based on cone theory is presented for representing and measuring sets of transversals in closed form. Then, the solution to the track coverage problem can be formulated as a nonlinear program (NLP). The numerical results show that this approach can improve track coverage by up to two orders of magnitude compared to grid and random deployme...