Fast Localizing for Anonymous UAVs Oriented Toward Polarized Massive MIMO Systems

The topic of anonymous unmanned aerial vehicle (UAV) localizing based on angle estimation has been frequently discussed in the past few years. However, the existing methodologies are inefficient in a massive sensor arrays scenario. To avoid such drawback, a cooperative 3-D positioning methodology is introduced. The critical idea of the proposed localizing method is to estimate the 2-D angle of the anonymous UAV via a polarized massive–multi-input multi-output (MIMO) system. To reduce the computational burden and explore the nature of the multidimensional data, a tensor compressive sampling (TCS) framework is proposed. Moreover, a closed-form estimation strategy is developed for 2-D direction finding. Our framework is shown to be more efficient than the existing algorithm in terms of hardware/software complexity. Besides, it is suitable for a polarized MIMO system with an arbitrary array geometry. Several simulation examples are provided to show its improvement of the new methodology.