###### Abstract  
Accurate localization is the premise of many technologies and applications, such as navigation, emergency assistance and wireless sensor network. For Global Navigation Satellite System (GNSS)-denied urban or indoor environments, various localization technologies based on mobile communication networks or other wireless technologies have been designed and developed. The main challenge for these localization technologies is the presence of a non-line-of-sight (NLOS) propagation environment due to dense obstacles or buildings. The virtual station method is a promising high-accuracy target localization technique in NLOS environments, and the localization of the scatterer is key to the virtual station method. Once one-bounce scattering signals from the same scatterer are identified, the localization of the scatterer can be achieved easily with the existing localization algorithm of line-of-sight (LOS) scenario, and then the localization of NLOS scenarios is converted into a problem of LOS easily. In this paper, a hybrid time of arrival (TOA)/angle of arrival (AOA) virtual station localization algorithm based on scattering signal identification is proposed. Firstly, one-bounce scattering signals from the same scatterer are identified based on TOA/AOA measurements. Next, scatterers are located based on one-bounce scattering signals with the LOS localization algorithm, and then scatterers are regarded as virtual stations and used for mobile station (MS) localization. Compared with the existing research on the virtual station method, the proposed algorithm relies only on TOA/AOA measurements and does not require any assumption or prior knowledge about the scatterer, base station (BS) or MS, which provides a solid foundation for feasible target localization. Simulation results demonstrate, as far as we know, the proposed algorithm outperforms the state-of-the-art hybrid TOA/AOA algorithm in localization accuracy. their combinations [11]. These algorithms are proved to be very effective for applying in open-air environments, in which the LOS signals are dominant. However, NLOS radio propagation between BS and MS generally exists in the localization scenarios, due to dense obstacles or buildings, which dramatically degrade the performance of localization algorithms. NLOS is considered the most severe source of positioning error [12]. NLOS propagation results in time and angle measurements error. For time-based localization systems, the extra propagation distance of the NLOS signal directly corresponds to an overestimate of the distance between the MS and BS, for direction-based localization systems, the angle from which the signal arrives at the MS is not in the true direction to the BS. This leads to severe degradation of localization accuracy if standard LOS localization estimation algorithms are employed. To mitigate the NLOS impact, a variety of techniques and algorithms have been proposed in the literature. Conventional methods to process the NLOS effect can be mainly divided into three categories. One category identifies and discards NLOS signals so that only the LOS signal is applied for localization [13; 14; 15]. This can achieve proper localization performance if the NLOS signals are detected correctly and the number of remaining LOS links is sufficient for localization (e.g., three LOS links of distance measurements for 2D scenarios and four links for 3D scenarios). This type of solution would be problematic in scenarios, where the LOS signal is not available due to the effect of ray blocking. The other category tries to mitigate the negative impact of NLOS measurements and exploits both LOS and NLOS signals, such as the residual-based method [16; 17; 18; 19] and NLOS propagation model compensation [20; 21; 22; 23; 24; 25].