An Interpolated Iterative Adaptive Approach for Scanning Radar Imaging

Angular superresolution has been widely applied to improve cross-range resolution for forward-looking scanning radar imaging. However, in the cases of low azimuth sampling rate, traditional methods fail to estimate off-grid targets accurately because of a lack of enough samples. Since the off-grid samples can be considered as missing data, off-grid samples could be reconstructed by exploiting the spectral characteristics of radar antenna patterns. Thus, an interpolated iterative adaptive approach (IAA) combined with spectral windowing is proposed to estimate off-grids targets as well as suppress high frequency noise. Simulation and experimental results have demonstrated higher angular resolution and positioning accuracy than traditional methods.