Adaptive CLEAN algorithm for millimetre wave synthetic aperture imaging radiometer in near field

High-resolution millimetre wave images of contiguous targets often suffer from the influence of sidelobe artefacts, partial correlation between targets and so on. Owing to the characteristics of near-field synthetic aperture imaging radiometers [such as the changing point spread function (PSF) and slender sideline], the existing CLEAN algorithms are unsuitable for near-field synthetic aperture imaging. This study is devoted to establishing a novel CLEAN algorithm (named adaptive CLEAN) to clean the reconstructed millimetre wave images accurately. First, the characteristics of near-field synthetic aperture imaging are studied. Then, the adaptive CLEAN algorithm is established based on these characteristics. In this study, the authors amend the amplitude of the targets and select the matching PSF for them according to their azimuths. Unlike other CLEAN algorithms, the parameters of this adaptive CLEAN algorithm are calculated by a formula, which is concluded from a lot of simulation experiments. Finally, the effectiveness of the proposed adaptive CLEAN algorithm is tested by several simulation experiments, and the superiority is also demonstrated by comparing it with the existing CLEAN algorithm. The results demonstrate that the proposed method is an efficient, feasible algorithm for cleaning the reconstructed images, irrespective of the point or contiguous targets.