Research On Direction Finding And Localization Technology Of Interference Source Based On UAV Platform

Global Navigation Satellite System(GNSS)has been widely used in military and civilian fields due to its wide coverage and low cost,and has become an indispensable and important facility in modern society.However,the GNSS satellite signals are relatively weak and navigation receivers are susceptible to sources of interference,which will pose a serious threat to the normal operation of the navigation system.To maintain the integrity of navigation system,it is necessary to accurately locate any interference source and take appropriate measures to remove it in time.Conventional ground-based detection equipment is highly dependent on the directional environment and is easily blocked by tall building clusters.Therefore,in order to achieve rapid response and flexible deployment of the system,we select UAV as a monitoring platform to detect and locate ground interference sources.The paper focuses on the optimization of the current direction finding algorithm and the improvement of the performance of the localization algorithm by using an unmanned aircraft with a uniform circular array antenna.The contribution of this research can be classified in four domains:(1)The first is 2D DO A azimuth and elevation angle estimation algorithm for multiple interference noncoherent sources.Considering that super resolution techniques like the MUSIC algorithms need a prior knowledge of number of sources to perform DO A estimation which limits their robustness,we propose a new high-resolution estimation method without the information of number of signal sources.The proposed method employs QR decomposition to extract the signal subspace instead of the computationally complex eigenvalue decomposition or singular value decomposition methods which are typically used in DOA estimation algorithms.It does not require knowing the number of sources in advance and pairs the estimated azimuth and elevation angles automatically for multiple sources.The simulation results show that the proposed method avoids estimation failure and provides better performance at a lower computational cost compared with the MVDR method.(2)In the second domain,considering that in a complex direction finding environment,due to multipath propagation and other reasons,there are a large number of coherent signals,resulting in the rank deficit of the source covariance matrix,which further degrades the estimation performance of the spatial spectrum algorithm.In order to achieve signal decoherence and recover the rank of signal covariance matrix,a fast decoherence algorithm based on virtual array translation is discussed.The algorithm realizes the signal decoherence of the uniform circular array without sacrificing the aperture of the array,and avoids the complex process of transforming into a virtual linear array.Simulation experiments verify the effectiveness of the method.(3)In the third domain,which is interference localization algorithm based on azimuth and elevation.Considering the highly nonlinear relationship between the measured value and the spatial position of the interference source in the location model,and some traditional localization algorithms have problems such as biased estimation and high computational complexity.Therefore,we propose a convergent iterative localization algorithm,which does not require any matrix operations,converges to any initial value and has better estimation performance under high noise level.Compared it with traditional localization algorithms through simulation experiments,the results of the simulations verify the superiority of the method.(4)Lastly,we develop an overall design scheme of the interference source direction finding system based on the UAV platform,which uses the UAV to carry the direction finding load to realize the DOA estimation of the interference source.In addition,the system is tested in the actual scene,and the performance of the localization algorithm is analyzed through the measured data.