UAV Acoustic Positioning System For Traffic Management And Control

In recent years,with the increasing maturity of drone technology,consumer-grade drones have achieved a spurt of development.The lagging industry regulations in the drone field has led to a series of "black flight" behaviors,posing a serious threat to personal privacy and national social security.The growing demand for drone regulation has led to a shift toward more accurate and efficient positioning technologies.With the advantages of low cost,high accuracy in proximity positioning and silent work,acoustic positioning UAVs have gained the attention of many scholars and have gradually become a hot spot for research on UAV "black flight".For the problem of UAV "black flight",the current acoustic detection technology still has defects in environmental noise interference and real-time.Since it is difficult to obtain UAV data directly and the array sampling data is small,this thesis firstly designs a multi-channel sampling system based on LabVIEW platform to collect and store UAV data,which provides data support for the algorithm development and verification later.Finally,based on the unique harmonic characteristics of rotor noise,we propose a harmonic-focused acoustic localization algorithm for UAVs,which enhances the signal-to-noise ratio and improves the localization accuracy of UAVs,in response to the poor localization effect of MUSIC and RSS focusing algorithms under low signal-to-noise ratio.The main research works are as follows:(1)Processing the UAV noise data by short-time Fourier transform and discrete Fourier transform to obtain the acoustic characteristics of the noise,and analyzing the harmonic frequency parameters in the noise signal according to the time-frequency,which lays the foundation for the harmonic focusing algorithm proposed in the later thesis.(2)A multi-channel sampling system is developed based on LabVIEW platform,which provides the data basis for the development and verification of the positioning algorithm in this thesis.The system supports multi-channel data storage,real-time signal spectrum display and other functions.After experimental verification,the system can realize the functions of data acquisition and signal analysis for low-altitude UAV.(3)An improved generalized correlation algorithm is proposed to solve the problem of time delay estimation failure of the generalized correlation function in the case of small signal energy.The algorithm is denominator-weighted for the PHAT function,which avoids the problem of increasing the error due to the small value of the mutual power spectrum of the signal between two channels.After numerical simulation and experimental verification,it is shown that the improved algorithm can accurately estimate the time delay value at low signalto-noise ratio and achieve high accuracy positioning of UAV.(4)In order to reduce the influence of environmental interference on the UAV positioning results,an acoustic UAV positioning algorithm based on harmonic focusing is proposed.The algorithm utilizes the unique harmonic law of rotor noise,focuses near each harmonic frequency point in the full frequency band of noise,focuses the harmonic information of the full frequency band at the reference frequency,eliminates the environmental noise and interference information,reconstructs the array reception matrix,and enhances the signal-tonoise ratio.The experimental results show that the algorithm effectively reduces the influence of interference and noise on the localization results,enhances the resolution of the UAV trajectory and improves the localization accuracy.