Research On Clustering Algorithm Of Emitter Based On Channel Estimation And Its Utilization

Emitter signal sorting is a key technology for electronic reconnaissance in modern electronic warfare.Emitter signal sorting refers to classifying the detected electromagnetic signals according to the emitter to which they belong.At present,the signal characteristic parameters are usually used to realize the emitter signal sorting,however,the channel characteristics contained in the electromagnetic signals from different emitters also have large differences factually.In this paper,we study the intelligent sorting method of emitters based on the differences in channel characteristics.This method is divided into two steps: first,the channel characteristics of the electromagnetic signal are extracted,and then the clustering technology is used to cluster the extracted channel characteristics to realize the emitter signal sorting.In view of the new ideas proposed in this paper,this paper mainly studies two aspects,one is the method of accurately extracting channel features,and the other is the study of clustering technology,and the research on clustering algorithms is carried out with the extracted channel impulse response as the object.In response to the above research content,the main research work of this paper is as follows:1.Overview of the technical scheme of intelligent sorting of emitter based on the differences in channel characteristics.Aiming at the shortcomings of the traditional methods,a new process for implementing intelligent sorting of emitter based on the differences in channel characteristics is proposed.The research problems are elaborated,the problem model is established,and the key problems and technical difficulties in the research content are analyzed.An overall scheme for implementing intelligent sorting of emitter based on the differences in channel characteristics is proposed.2.Blind estimation of channel impulse response based on intercepted signals.The blind channel estimation studied in this paper has two major difficulties: one is that there is no training sequence,and the other is that it does not know any prior information including signal patterns,codes,etc.In this paper,through the study of blind channel estimation technology,a blind equalization algorithm is selected,which can achieve channel equalization under non-cooperative reception conditions.On this basis,a channel feature extraction scheme based on blind equalization algorithm is studied.This scheme can effectively extract the channel impulse response in both simulation experiments and actual measurement experiments.When the signal-to-noise ratio is above 10 d B,the channel impulse response extracted by this scheme reaches a high accuracy.3.Cluster analysis of emitter based on channel impulse response.The working principle,applicable conditions,advantages and disadvantages of several commonly used clustering algorithms are studied.Based on the target requirements of this design and the characteristics of the channel impulse response data set,two clustering algorithms,DBSCAN and BSAS,were selected to sort the emitter signals.Both of these algorithms have achieved high sorting accuracy in simulation experiments.In the follow-up,the results of simulation experiments,the advantages and disadvantages of the two algorithms,and the influence of parameter selection on the separation results are discussed in conjunction with the simulation experiment results.4.Verification of intelligent sorting test of emitter based on the measured system.This paper designs a set of measured tests based on the Yun SDR platform.On this basis,an intelligent sorting scheme for emitter based on measured data is given.The actual test verifies the effectiveness of the scheme.This scheme has achieved a high sorting accuracy in the tested experiments.Finally,the factors that cause the channel change are verified through experimental analysis,and the scope and limitations of this scheme are given.