Research On Satellite Navigation Interference Feature Recognition Technology

Since its creation,satellite navigation technology has attracted wide attention from various countries due to its strong high coverage,high precision and high convenience.Countries around the world are also rushing to develop their own satellite navigation system,such as the US GPS,Russia's GLONASS and China's Beidou navigation system.Today,the scope of the battlefield has been further extended from the ocean,land and sky to outer space.The future war will be a war of integration of land,sea,sky and outer space.Therefore,the research of satellite navigation systems is particularly important.With the continuous development of the times,the working environment of satellite navigation receivers is more and more complex,and satellite navigation signals are highly susceptible to external signal interference,such as unintentional interference,suppressed interference,deceptive interference,and combined suppression and deception.This greatly affects the performance of the satellite navigation receiver.Therefore,it is urgent to study key technologies and engineering application systems that are effective,accurate,and rapid detection,identification,and positioning.It is extremely important to improve the anti-jamming performance of the satellite navigation system for the fast recognition of the interference signal source encountered in the satellite navigation process.The main work of this paper is as follows:1.Summarize the typical interferences encountered in the current satellite navigation signal transmission process,classify six kinds of interference signals,establish a mathematical model of each interference signal,summarize each interference characteristic and simulate the interference signal,and use the signal time domain.,frequency domain,time-frequency domain analysis method to extract signal feature parameters normalized frequency domain 3dB bandwidth,spectral kurtosis coefficient,frequency domain impulse partial standard deviation,Fourier domain energy concentration degree,fractional Fourier domain impulse Five characteristic parameters such as partial standard deviation.Aiming at the problem that the feature of the composite form interference signal is difficult to be identified in the interference feature recognition problem,it is proposed to use the independent component analysis method(PCA)to separate the compositeinterference signal into multiple single interferences.The PCA method is verified by simulation.It has a good separation effect on the composite interference signal.When the traditional ICA algorithm FastICA solves the optimal solution by Newton's method,the constraint factor is introduced to reduce the number of iterations of the algorithm to ensure that the algorithm reaches convergence faster.3.Research and design satellite navigation interference source classifier.Based on the traditional decision tree classification algorithm,according to the deficiency of the decision tree classification algorithm in manually setting the threshold threshold,the KNN and SVM algorithm combined with the decision tree algorithm are used to improve the classification algorithm.The accuracy of recognition.The simulation results of three algorithms are compared.The experimental results show that the satellite navigation interference source classifier combined with SVM has the best classification performance based on the decision tree classification model.