Study On ISAR Translation Compensation

Inverse Synthetic Aperture Radar (ISAR) is attracting more and more attention in the world, and is becoming a new research field in signal processing.This thesis firstly introduces the principle of ISAR and its imaging algorithms. They are important fundamentals for the research here. Here we only discuss the Range-Doppler algorithm for ISAR imaging. ISAR uses the relative motion between the radar and the target to image the target. If we consider only the rotation of the target around the origin, then the imaging process has two steps: range resolution and azimuth resolution. If consider the translation between the radar and the target, then before azimuth resolution, translation compensation has to be carried out to remove the effect of the translation.Translation compensation is a key step in ISAR imaging. This thesis is aimed towards a research of the technologies of translation compensation. It consists of range alignment and phase adjustment. There are many methods of translation compensation.Range alignment is the former step of phase adjustment, so improving the quality of it has a significant meaning. This thesis introduces the maximum-correlation method for range alignment. The maximum-correlation method shifts an echo such that the correlation function of its envelope with a reference envelope is a maximum. The range shift obtained in the traditional method is an integer. However, the actual range shift may not be an integer. It means that even if two echoes are correctly aligned, there may still be an error of up to half a range bin. This paper presents an improved method. First, the range shift is estimated according to the derived frequency-domain expression of the correlation function. Then, the echo is shifted by introducing a phase ramp in the frequency domain. This method overcomes the limitation of integer steps and improves the accuracy of range alignment. This thesis use filed data to evaluate our method. The results show that the improved maximum-correlation method leads to better images due to more accurate range alignment, which means the improved method is effective.