Aliasing-free high resolution imaging of fast rotating targets with narrowband radar

Abstract

Narrowband radar has been successfully used for high resolution imaging of fast rotating targets by exploiting their micro-motion features. In some practical situations, however, the target image may suffer from aliasing due to the fixed pulse repetition interval (PRI) of traditional radar scheme. In this work, the random PRI signal associated with compressed sensing (CS) theory was introduced for aliasing reduction to obtain high resolution images of fast rotating targets. To circumvent the large-scale dictionary and high computational complexity problem arising from direct application of CS theory, the low resolution image was firstly generated by applying a modified generalized Radon transform on the time-frequency domain, and then the dictionary was scaled down by random undersampling as well as the atoms extraction according to those strong scattering areas of the low resolution image. The scale-down-dictionary CS (SDD-CS) processing scheme was detailed and simulation results show that the SDD-CS scheme for narrowband radar can achieve preferable images with no aliasing as well as acceptable computational cost.