Unmanned aerial vehicle identification method based on brain-like auditory model

The invention discloses an unmanned aerial vehicle identification method based on a brain-like auditory model, and belongs to the technical field of cognitive automatic control. An unmanned aerial vehicle recognition method based on a brain-like auditory model simulates a coding mechanism, a feature binding mechanism and a selective attention mechanism of an auditory nervous system of a human brain to establish an unmanned aerial vehicle sound recognition model, achieves the effect that the human brain can distinguish target sound in a complex scene and a low signal-to-noise ratio environment, and judges the type of an unmanned aerial vehicle. The method can be well competent for unmanned aerial vehicle detection with low flight height, slow flight speed and small radar scattering area in a complex environment, and has the advantages of high accuracy, low false alarm rate and low power consumption similar to a human brain auditory nervous system. 本发明公开了一种基于类脑听觉模型的无人机识别方法，属于认知自动控制技术领域。一种基于类脑听觉模型的无人机识别方法，模拟人脑的听