Based on the clustering of the coherent superposition frequency diversity array radar target imaging method

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.