Intelligent Unmanned Defense System for Autonomous Interception of UAVs Based on Improved Acoustic Source Localization Algorithm

Illegal flights of UAVs have seriously threatened personal privacy and social security. UAV localization techniques, especially acoustic source localization, have received extensive attention from scholars. However, the traditional acoustic source direction of arrival (DOA) estimation algorithms are reconstructed using only the cross-correlation or covariance matrices of part of the array received data. This leads to insufficient information utilization for high-precision localization and interception. Therefore, this article proposed a UAV acoustic source localization algorithm based on the ESPRIT algorithm with Toeplitz matrix reconstruction. We conducted simulation tests on multiple UAV acoustic source signals in different directions. We have derived the relational equation between the number of multiple UAV acoustic source signals and the minimum incidence critical angle. The results demonstrated that the proposed algorithm has minimum RMSE and high DOA estimation signal accuracy. The resolution probability of the algorithm even exceeds 95%. We applied the improved algorithm to the indoor and outdoor tests of a self-designed 12-channel spherical microphone array and a circular MEMS microphone array. The effectiveness of the proposed algorithm and the accuracy of the derived equations are verified. Finally, we designed an intelligent interception unmanned defense system and applied it to different locations. The results show that the improved algorithm proposed in this article is correct and feasible.