摘要: Inverse synthetic aperture radar (ISAR) imaging has been widely developed and applied in many applications, such as, radar target recognition, autopilot and seaport ship surveillance, etc. However, low signal-to-noise ratio (SNR) ... 展开 Inverse synthetic aperture radar (ISAR) imaging has been widely developed and applied in many applications, such as, radar target recognition, autopilot and seaport ship surveillance, etc. However, low signal-to-noise ratio (SNR) environments may impede conventional range profiles-based translational motion compensation (TMC), causing image degradation. In this paper, a novel method combining profiles and phase is proposed which utilizes two-dimensional (2-D) coherent accumulation to overcome the low SNR problem, even when the range profiles are submerged into noise. The method only requires Fast Fourier transform (FFT) and Hadamard multiplication operations which renders it suitable for real-time applications. Simulation results are provided to validate the performance of the proposed TMC method compared with the state-of-art TMC methods. 收起