基于聚类相参叠加的频率分集阵列雷达目标成像方法 postprint

Abstract: Aiming at the problem of blurred target position and high sidelobe when the back projection algorithm (BP algorithm)
is imaging multi-targets, after analyzing the accumulation characteristics of the FDA target echo amplitude, a target
imaging method of frequency diversity array radar based on clustering and coherent superposition is proposed. In the analysis
and Simulation of BP algorithm imaging process, it is found that the target point has the characteristics of energy concentration
and energy difference with the virtual image point. The K-means clustering algorithm can make full use of these characteristics
of the target point to extract and classify the target points in the radar imaging area, and only compensate the time
delay of the grid points of the specific cluster after classification, and then stack the echo amplitude, Thus, the energy value
of the time delay compensation grid points in the imaging region is obtained, and finally the multi-target clear two-dimensional
imaging is realized. The simulation results show that the proposed method can effectively solve the problems of fuzzy
position and high sidelobe when BP algorithm imaging multi-target, and improve the accuracy of imaging results.