Simultaneous Velocity Estimation and Range Compression for High Speed Targets ISAR Imaging Based on the Chirp Fourier Transform

摘要

High speed targets (e.g., aircraft, satellite) imaging is crucial for air traffic safety and space surveillance. Based on the target motion model, the characteristics of the multi-component linear frequency modulation (LFM) signal caused by the high speed motion are analyzed in detail. Furthermore, a novel method based on the chirp Fourier transform and Shannon minimum entropy principle for high speed targets Inverse Synthetic Aperture Radar (ISAR) imaging is proposed. Firstly, according to the velocity scope, the chirp rate interval is established. Secondly, the corresponding phase term is constructed to compensate the quadratic phase term caused by the high speed motion. After the range compression, the range profile with minimum entropy is regarded as the optimal compensated profile, and finally the required ISAR image is formed by the cross-range compression. The simulation experiments demonstrate that the proposed method can obtain better ISAR images than the classic range doppler algorithm and fractional Fourier transform algorithm.