Research And Deployment Of Software Components Of Software Radar

In recent years,the traditional radar signal processing platform architecture is constantly upgrading and developing towards the open system architecture and forming the software radar.This article analyzes the development trend of the radar in the new era,excavates the changing trend of radar demand and problems of traditional radar,and demonstrates the prospect and significance of componentization of the software radar information processing platform(SRIPP).The architecture of SRIPP and various technologies used were investigated,and the development status of such technologies at home and abroad was explained.Finally,refer to the existing technical achievements globally and determine the overall design of the SRIPP.Combining the requirements of radar tasks,this article first analyzes the system architecture of the SRIPP,determines the hardware resource layer,the basic software layer,the application support layer and the radar application layer,and explains the functions and interactions of each layer.Then the design scheme of hardware architecture and software architecture was proposed.Then,this article researched component technology,determined the model and development process,designed a component management framework and clarified requirements for applications to access operating systems and component management frameworks,and the design requirements of the application program interface.Subsequently,this paper studies the middleware layer of the radar information processing platform.The functions of the middleware layer are analyzed,and DDS is used as communication middleware and VSIPL is used as the computing middleware.Finally,the deployment strategy of software components in distributed blade servers is studied.Based on the genetic algorithm,an intelligent deployment strategy is designed to optimize the distribution and deployment of software components so that the distributed system can achieve load balance and operate efficiently.The simulation results show that the intelligent deployment strategy can allocate system resources better than round-robin scheduling strategy.