Research On The Technology Of Low-RCS High-velocity Target Detection And Tracking For Airborne Radar

It's of great military value to employ the airborne radar to detect and track the moving target with low RCS and at high velocity. The technology of low-RCS high-velocity target detection and tracking for airborne radar is studied by this dissertation. The problems of optimal radar waveform design, ground clutters suppression, new target detection method and tracking method are analyzed.To the characteristic of low-RCS high-velocity target detection for airborne radar, a new radar waveform scheme is proposed, which employs the constant carrier frequency coherent pulse sequence signal as the basic waveform to detect high-velocity target and the LFM pulse sequence signal as the accessorial waveform to measure the range with high resolution. The parameters of the airborne radar are decided.The model of ground clutter is set up, and the familiar clutter suppression methods such as AMTI, DPCA, STAP and CSI are discussed. A modificative CSI method which does not need to get the information of radar platform velocity from the navigation device is proposed. Simulation and real data processing prove the validity of the new method. To the characteristic of low-RCS high-velocity target detection for airborne radar, a new ground suppression scheme which employs both AMTI and CSI is given. The TBD algorithm based on dynamic programming (DP-TBD) is applied in the detection of moving target with low RCS and high velocity for airborne radar. The process of it is given and the computer simulation proves the validity. The performance of the applying DP-TBD in the airborne radar is analyzed and the results prove the new method's advantage to the traditional method which employs the data from only one scan.After the establishment of radar measure model and target maneuvering model investigated and the filter algorithm discussed, a scheme of tracking high-velocity maneuvering target by airborne radar is proposed, which employs measure coordinate conversion method to establish measure model and then use the three models (CV,CA and current statistic model) Interacting Multiple Model Algorithm to filter the data. The validity of it is proved by the computer simulation.