Analysis And Extraction Of Radar Characteristics For Midcourse Ballistic Missiles

Analysis and extraction of radar characteristics of Midcourse Ballistic Missiles was studied in the dissertation against the background of target recognition in ballistic missile defense (BMD) systems. Payload deployment is an important event during the flight of ballistic missiles in Midcourse. The detection of the deployment avails the process control of the ballistic missile defending, and more effective distribution and utilization of the resource of radar detecting power can be achieved. The discrimination of warheads from heavy decoys is a key problem in the BMD system.The detection of payload deployment and the identification of warheads and heavy decoys have been studied, mainly including three facets:Firstly, a mathematical model of the payload deployment course in Midcourse was established according to the law of conservation of momentum, and the radar echo model during the course induced. The payload deployment course can be detected by identifying the change of the Doppler frequency, so a method using the maximal Cross-correlation function was proposed to detect the payload deployment course. The effectiveness of the method has been testified with simulation.Secondly, the precession motion of ballistic missiles in Midcourse was analyzed and modeled, indicating that the inertia ratio could be used to distinguish warheads from heavy decoys, and the relation between the precession period and inertia ratio was induced. After analysis of the influence by the precession motion of ballistic missiles on their Radar Cross Sections (RCS), the relation between the precession period and RCS period was presented. With the fluctuant characteristic taken into account, a detailed model for RCS time sequences of precessing targets was established.Thirdly, on account of kinds of disturbing in the RCS-time sequences of BMs, a Low pass Filter (LF) and a Homomorphic Filter were designed to filter noise. Furthermore, Circular Average Magnitude Difference Function was proposed to extract the precession period from filtered RCS-time sequences. And finally, simulations on the precession period extraction method with different Signal to Noise Ratio (SNR) were provided with error analysis on the simulation results.Lastly, the thesis was summarized with directions of further work pointed out.