Conventional localization of unmanned surface vehicle (USV) predominantly relies on a single integrated navigation system, typically comprising a global navigation satellite system (GNSS) and an inertial navigation system. However, the GNSS signals are vulnerable to external perturbations, which can substantially compromise the positioning accuracy. To achieve high-precision positioning of USV, this article investigates the cooperative localization problem for a class of USV in peer-to-peer heterogeneous sensor networks. A cooperative consensus localization (CCL) algorithm is proposed for the USV operating within heterogeneous sensor networks composed of ultra wideband modules and an integrated navigation system. The algorithm adopts a consensus-based state estimation approach founded on the principle of consensus on information. By integrating these methodologies, the proposed CCL algorithm enables high-precision localization of USVs, even in the presence of unknown inputs originating from the integrated navigation system. Furthermore, the stability of the proposed CCL algorithm is guaranteed under mild assumptions, including bounded system parameters, the doubly-stochastic property of the weight matrix, and connectivity in the heterogeneous sensor network. Specifically, the estimation error of each estimator remains uniformly bounded in the mean-square sense. Finally, the effectiveness and superiority of the proposed technique are validated through both numerical simulations and practical experiments.