Research On ISAR Imaging Technology Under Low SNR Condition

Inverse Synthetic Aperture Radar(ISAR) imaging is one of difficulties in the field of radar imaging, and is of great significance for both scientific and applied purpose. In this paper, the speed compensation technology, the pre-process technology of the High Resolution Range Profile(HRRP) and the auto-focusing technology in low Signal to Noise Ratio(SNR) condition have been researched, respectively.In the introduction, the context and the significance of the study of ISAR imaging technology at low SNR have been illustrated, and the development of the high resolution wideband radar and ISAR imaging technology have been reviewed. Finally, the overview of this paper has been introduced.In the study of the speed compensation technology, the signal model of the space target with high speed has been derived, so as to numerically analyze the effect of speed to HRRP. Then, the speed compensation algorithms based on the Cubic Phase Function(CPF) and the Integration Cubic Phase Function(ICPF) have been proposed, respectively. Finally, the experimental results based on both simulated and darkroom measured data have verified the effectiveness of the presented methods.In the study of the pre-process technology of the HRRP, firstly, the signal model of the HRRP of the target in the condition of the white Gaussian noise has been derived, and the Pseudo Matched Filter(PMF) has been defined. Then the HRRP pre-process algorithm based on PMF has been proposed to improve SNR of the HRRP. Finally, the performance of the proposed method has been validated by the experimental results based on both simulated data and radar measured data. According to the experimental results, the proposed method can improve SNR of the HRRP by 5-10 dB.In the study of the auto-focusing technology, the minimum entropy auto-focusing methods based on the Newton Iteration(NI) method, the Simplified Newton Iteration(SNI) method and the Newton-Shamarskii Iteration(N-SI) method have been proposed, respectively, so as to improve the computational efficiency of the auto-focusing method based on minimum entropy criterion. The experimental results based on both the simulated data and the radar measured data have verified the effectiveness of the proposed methods.In the last part, the work of the dissertation has been summarized, and next step of the study has been presented.