Research On Radar Signal Sorting Algorithm Based On Data Filed And Cloud Model

The mainstream form of future warfare is information-based warfare in the form of electronic warfare.Radar signal sorting,as an important part of electronic reconnaissance,is largely related to whether electronic warfare can play a role and ultimately affect the direction of war.However,with the continuous improvement and development of science and technology,the number of radars has increased dramatically,the radar system has become richer and richer,and the electromagnetic environment of radars has become more and more complex and changeable.These phenomena will cause the radar parameter information to be similar or change,and the radar signal distribution will be dense.Overlap,clutter interference,etc.,put forward higher requirements for radar signal sorting technology.From the perspective of the urgent need for radar signal sorting,this paper mainly studies the radar signal sorting technology in a complex electromagnetic environment.The main research contents are reflected in the following aspects:First analyze and understand the complex electromagnetic environment in which radar signal sorting is located,and explain the overall system structure of radar signal sorting and their respective functions,introduce the characteristic parameters required for radar signal sorting,and discuss several traditions.Radar signal sorting algorithm for detailed interpretation and analysis.Secondly,it mainly introduces the theoretical basis of data field clustering and decision graph clustering algorithms,and makes different improvements to both clustering algorithms to improve the clustering effect of the algorithm.The data field is based on the potential value of the data object in the field to automatically cluster the data objects,and uses the value of the potential value function to handle isolated noise points.The decision map is based on the local density value of the data object and the distance to the nearest large density point.Determine the cluster center and the number of clusters.Then,the data field and the decision map are jointly clustered,and the potential value and the distance to the nearest large-density point are used for clustering.The simulation results show that the clustering accuracy of the joint clustering is higher.Then,based on the missed and missed pulses,the cloud object modeling is used to evaluate the data objects to improve the missed and missed pulses.The SDIF algorithm is improved to eliminate the disadvantage of not being able to handle jitter signals,and to achieve the main sorting function of radar signals.Finally,the cloud model and the improved SDIF algorithm are jointly simulated.The simulation results show that under the condition that the radar parameter information is close to each other and pulse interference,the joint sorting can obtain better sorting results.