Reseach And Implementation Of Unmanned Aerial Vehicle Passive Detection System With Intelligent Acquisition Of Weak Sound Source

In recent years,military drones and civil drones have developed rapidly.With the rapid increase in the number of drones,effective detection of drones is increasingly important.At present,the research directions of detection technologies for UAVs mainly include traditional radar,sound detection,and infrared detection.Among them,radar detection systems are the most widely used.In addition to traditional radar detection systems,acoustic detection systems have also received extensive attention.The sound detection system has certain advantages in target recognition,system cost,etc.Therefore,it is of great significance to research the unmanned sound passive detection system.When the UAV is running,it will naturally radiate acoustic signals.Through the analysis of the collected drone sound signals,the UAV target can be identified and located.This paper mainly studies the sound-passive detection system of UAV.Firstly,it studies the current common speech recognition algorithms,and analyzes and contrasts the various sound recognition algorithms for UAV sound signals.The voice signal recognition of the machine is based on the MFCC and neural network,and the UAV sound signal recognition scheme is combined.The identification scheme is verified by experiments.At present,the passive acoustic localization system can be divided into two major categories: direct and indirect.The main research of this paper is the positioning system of pickup arrays based on generalized cross-correlation delay estimation algorithm.This system belongs to indirect positioning system.The time delay estimation algorithm and the microphone array were studied separately and verified experimentally.This paper has completed the hardware and software design and implementation of drone sound passive detection system,mainly including the following four parts:(1)research and design and implementation of weak sound source data acquisition and transmission system based on STM32F103RCT6 microcontroller.(2)The research and implementation of UAV sound signal identification scheme combining MFCC and artificial neural network.(3)Research and implementation of UAV acoustic passive positioning system based on generalized cross-correlation and microphone array.(4)The design of the upper computer software system based on C# Winform.Among them,the weak sound source data acquisition and transmission system based on STM32F103RCT6 microcomputer includes weak sound source data acquisition circuit design,single-chip data acquisition software design and single-chip microcomputer and upper computer data communication.The UAV sound target identification and location algorithm is implemented in the host computer data processing system.The system structure is a master-slave structure composed of upper and lower machines.It is mainly composed of a sensor array and a host computer.The data acquisition system consisting of a single chip microcomputer and a sensor array is responsible for data acquisition and transmission.The system completes the identification and positioning of UAV targets.Finally,this dissertation completes the sound passive detection system of UAV and carries out experimental verification.