In this paper, we have addressed the hybrid RSS/AoA target localization problem in both noncooperative and cooperative 3-D WSNs, for both cases of known and unknown PT values. We first developed a novel nonconvex objective function from the RSS and AoA measurement models. For the case of noncooperative localization, we showed that the derived objective function can be transformed into a GTRS framework, by following the SR approach. Moreover, we showed that the derived nonconvex objective function can be transformed into a convex objective function, by applying the SDP relaxation technique in the case of cooperative localization. For the case in which PT is not known, we proposed a three-step procedure to enhance the estimation accuracy of our algorithms. The simulation results confirmed the effectiveness of the new algorithms in a variety of settings. For the case of noncooperative localization, the simulation results show that the proposed approaches significantly outperform the existing approach, even for the case wherein the proposed estimators have no knowledge of PT. For the case of cooperative localization, we have investigated the influence of N, M, and R on the estimation accuracy. For all considered scenarios, the new estimators exhibited excellent performance and robustness to not knowing PT.