Research And Implementation Of Pipeline Real-time Data Processing System For Low, Small And Slow Radar

Low altitude,small radar cross-section(RCS)and slow speed(LSS)targets have the characteristics of small RCS,inconspicuous Doppler characteristics,and low-altitude activities.In order to achieve normal detection and tracking of the LSS targets,the corresponding threshold and threshold value need to be reduced,and a large number of environmental clutter and interference targets will spontaneously enter the radar data processing system,which greatly increases the amount of data that needs to be calculated.Therefore,higher requirements are placed on the real-time performance and stability of the radar data processing system.In this paper,a pipelined parallel processing algorithm for radar data based on Pulsed Doppler(PD)system radar is studied,and a multi-platform portable radar control and display integrated upper computer software system is implemented based on Python programming language.The following are the main points of this paper:Firstly,this paper introduces the background and research status of LSS targets and radar data processing,including basic methods and principles.According to the overall plan of the radar system,the design idea of software modularization is used to complete the designing scheme of radar upper computer software system,such as UI module,Radar data process module,Interface module and Data transform module.Secondly,focusing on the characteristics of small RCS,large environmental interference,and indistinguishable spectral characteristics from clutter,this paper gives the implementation details in core algorithms in the radar data processing module.Among them,the sliding window selection mechanism based on the sector data structure is the innovation point of this paper,this innovation point can reduce the amount of calculation and caching data and improve the search correlation range of the point aggregation algorithm.In addition,directing at the high maneuverability for LSS targets,an experimental track repairing submodule is designed to splice interrupted tracks,joint missing points in tracks,and repair the tracks with abnormal values.Thirdly,due to the need to calculate a large amount of radar data,a pipelined real-time processing mechanism is used in the radar data processing module to improve the parallel processing capability,real-time performance and stability.Moreover,in this paper,some optimum schemes of algorithm optimization,for example,vectorization and grouping method,are given to improve the computing efficiency of the upper computer system,this optimum scheme can reduce the complexity of interconnection operations such as dot-to-dot interconnection,dot-to-track interconnection,and so on.Finally,this paper analyzes the algorithm complexity of each sub-module in the radar data processing module in depth,and gives the time-consuming test results of each module and accuracy analysis.The test results show that the pipelined real-time parallel processing mechanism can improve the real-time performance of radar data processing,and this optimum method effectively improves the computing efficiency of the interconnection algorithm.