Abstract
Doppler Radar Tomography (DRT) relies on spatial diversity from rotational motion of a target rather than spectral diversity from wide bandwidth signals. The slow-time k-space is a novel form of the spatial frequency space generated by the relative rotational motion of a target at a single radar frequency, which can be exploited for high-resolution target imaging by a narrowband radar with Doppler tomographic signal processing. This paper builds on a previously published work and demonstrates, with real experimental data, a unique and interesting characteristic of the slow-time k-space: it can be augmented and significantly enhance imaging resolution by signal processing. High resolution can reveal finer details in the image, providing more information to identify unknown targets detected by the radar.
Highlights
Tomography is a general imaging technique that is based on lower-dimensional projections of an object from different spatial aspects, which are processed using the projection-slice theorem [1]to reconstruct an image of the object
The slow-time k-space processing technique as presented in this paper provides a complimentary approach to traditional high-resolution inverse SAR (ISAR) imaging
With two datasets, the ability to improve image resolution using a rotating target with an ultra-narrowband radar
Summary
Tomography is a general imaging technique that is based on lower-dimensional projections of an object from different spatial aspects, which are processed using the projection-slice theorem [1]to reconstruct an image of the object. The well-known synthetic aperture radar (SAR) and inverse SAR (ISAR) imaging techniques may be described as two special forms of wideband tomography, in which another system resource—spatial diversity—is exploited only minimally [2]. Range-Doppler ISAR imaging, and stripmap SAR in particular, typically involve aspect angle changes of a few degrees [3,4,5]. This constraint of small rotation angles in the linear phase regimes allows the image inversion processing to take advantage of the computationally efficient fast Fourier transform (FFT) without needing signal interpolation onto rectangular grids. The target’s effective rotation vector Ωe is defined as the projection of the target’s total rotational velocity vector Ω along the x3 -axis
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
