Identification And Location DF Multi-navigation Interference Sources

The strength of satellite navigation signal reaching the ground is weak(about-160 DBM),which is easily suppressed by various kinds of active and passive electromagnetic interference.Especially in the area of complex electromagnetic environment,the navigation receiving terminal may receive one or several kinds of in band interference at the same time,which leads to the failure of satellite navigation receiver in the local area to complete the acquisition and tracking of useful signals,thus leading to positioning failure.Therefore,this paper will carry out the research of satellite navigation multi-interference signal source positioning technology,through the detection of the location failure area,complete the screening and elimination of all kinds of system interference sources,and focus on the multi-interference source identification and multi-interference source positioning problems in the above problems.The main work is as follows:First,this paper combs the types and systems of common satellite navigation interference signals,establishes their corresponding signal models,and analyzes the characteristics of various signals respectively;discusses the general methods of interference signal location,and determines the TDOA location mode of using multiple stations to observe multiple interference sources according to the characteristics of common satellite navigation interference signals;and puts forward the mode suitable for most satellite navigation interf-erence signals The time-domain cross-correlation feature extraction method of interference signal system can directly obtain the time difference information of multiple interference signals arriving at each monitoring station through time-domain cross-correlation,which is convenient for hyperbolic positioning,on the other hand,it has the advantages of small calculation and high precision of time-delay measurement.Second,this paper studies two machine learning classification methods based on support vector machine multi classification and convolution neural network.It classifies and identifies different correlation peaks in the cross-correlation graph,identifies the types and quantities of each interference signal from the multi-interference signal correlation graph,labels the corresponding TDOA information,and completes the classification of the same interference signal TDOA information,which can be used to realize the classification of the same interference signal TDOA information Location of each interference source.Compared with the traditional recognition method of feature matching,it can effectively complete the recognition when the spectrum of multiple interference sources is staggered or overlapped.Third,a typical simulation scenario of multiple interference sources is built to simulate the generation of corresponding if echo signals of multiple monitoring stations.The process of location and calculation of multiple interference sources,such as generation of cross-correlation chart,peak detection and TDOA extraction,classification and identification of interference signals,and location and calculation of TDOA,is simulated.The location performance of multiple interference sources is analyzed through simulation,and the relationship between location accuracy and signal-to-noise ratio of interference signals is discussed.