Drones or unmanned aerial vehicles (UAV) are remotely piloted aircrafts which are very popular for commercial and public-safety applications. However, they can impose several security threats such as espionage and terrorism-related activities. In this way, we propose a multidimensional antenna array based framework in order to accurately localize UAVs in multipath environments. Specifically, we extend a previous framework for signal emitter localization in two aspects: (i) by adopting a tensor representation to better exploit the structure inherently multidimensional of the data, and (ii) by including a multiple denoising preprocessing scheme to increase the signal-to-noise ratio of the received signal. Numerical results show that the proposed approach presents both lower position coordinate errors and spatial frequency errors when compared to the matrix-based and tensor-based techniques with spatial smoothing as denoising preprocessing step.