Research On Parameter Estimation Of Frequency-Hopping Signal In Impulse Noise

Frequency hopping(FH)is an important way of spread spectrum communication technique characterized by networking capabilities and strong anti-jamming.Therefore,FH signals have been applied widely in military and civilian communications,and the research of FH signals parameter estimation methods have become a hotspot in the study of spread spectrum communication.In traditional signal processing,the Gaussian distribution is used to be the background noise model,however,lots of researches show that the noise usually appears with notable impulses in the actual applications such as radar,communication,underwater sound,biomedicine and econometrics.This kind of non-Gaussian noise with more significant peak pulse waveform and thicker tail can be described accurately by alpha stable distribution.In alpha stable noise environment,the conventional signal processing methods based on Gaussian assumption are no longer applicable.In view of this question,a systematic study on parameter estimation of FH signals in alpha stable noise environment is carried out.The major work is outlined as follows:1.This thesis introduces the nature and main features of STFT and WVD.STFT overcomes the shortcomings of traditional Fourier transform,but it can not take time resolution and frequency resolution into account at the same time.WVD has the advantages of high time-frequency concentration,but it is diff-icult to effectively estimate FH signals parameters due to the cross-item interference.In view of the problem that WVD suffers from the effect of serious cross terms and parameter estimation precision is reduced in FH signals processing,the CWD and S-Method distributions are introduced,and their principle and main properties of suppressing cross term are analyzed.Then,on the basis of time-frequency distribution,the time-frequency characteristics of alpha stable noise are also analyzed.Based on the theory of mathematical morphology,a new method based on Adaptive Joint Image(AJI)filtering is proposed in an alpha stable noise environment.The method can obtain a clearer time-frequency distribution,which preserves the basic characteristics of FH signals and can effectively estimate the parameters of FH signals.2.In view that the conventional methods for FH signals parameter estimation suffer from performance degradation in impulse noise environment,the Nonlinear Amplitude Transform(NAT)method is introduced from the point of suppressing the amplitude of the pulse.Two NAT functions are described,then analysis and comparation are made on their noise suppression effects.On this basis,a new NAT function is proposed to preprocess the observed signals,which can suppress the large amplitude pulses of the noise and preserve the information of FH signals.Simulation results show that this method has better performance in suppressing alpha stable noise and it is easy to realize.3.A method of FH signals parameter estimation based on alpha stable noise sparsity and optimal match is proposed.It is analyzed and concluded that the spike pulses of the alpha stable distribution noise approximately meet sparse conditions,by using the differences of the characteristics in the time domain,FH signals and the noise can be easily separated,and the goal of suppressing noise can be achieved.Under the framework of compressed sensing,the three-parameter dictionary is constructed based on the characteristics of FH signals,then the Optimal Match(OM)for adaptive FH signal decomposition is used to obtain the matching atoms and the FH signal parameters are estimated based on the information contained by these time frequency atoms.Simulation results show that compared with the conventional FH signal parameter estimation methods,the proposed method(SOM),which uses noise sparsity to suppress the noise and then adopts the OM algorithm,has improved the estimation accuracy of FH signals parameter and it is more robust to the alpha stable distribution noise.