The invention discloses an unmanned aerial vehicle real-time identification and
tracking system based on a neural network, and the
system carries out the identification and tracking of a target unmanned aerial vehicle through the fusion of a
millimeter-
wave radar and a
network camera, i.e., obtains a three-dimensional target coordinate through the
millimeter-
wave radar, achieves the all-
weather monitoring of the target unmanned aerial vehicle, and achieves the real-time identification and tracking of the target unmanned aerial vehicle through the combination of an image recognition module of the
network camera. The method achieves the precise recognition and confirmation of the type and position of a target, and improves the robustness and recognition accuracy in a complex environment. A closed-loop multi-strategy holder
control algorithm is adopted, a tracking control module of the
server is fused with three control strategies of proportion, fuzzy and integral differential adjustment, a holder control instruction is calculated in real time according to the target state, accurate turning and continuous tracking of a camera are achieved, the stability of the target unmanned aerial vehicle kept in the center of a picture is improved, and the target unmanned aerial vehicle is more stable. The requirements of continuous, stable and closed-loop tracking of the unmanned aerial vehicle in a complex dynamic environment are met, and the
system has the technical advantages of being high in
adaptive capacity, high in response speed and high in recognition precision.