HF radar signal processing based on tomographic imaging and CS technique

This study presents the application of a spotlight-mode synthetic aperture radar (SAR) imaging technique to the problem of high probablity target detection in high frequency (HF) radar system, attempting to improve its spatial resolution. The effects of finite aperture on resolution, sampling constraints and reconstruction over a complete angular range of 360 degrees are discussed. A Convolution Back Projection (CBP) algorithm has been applied to image reconstruction. In order to solve the range limitation of aspect angle with one radar-carrying platform, we collect data over a larger azimuthal range by making multi-aspect observations. Each straight line is a sub aperture over which we can perform the CBP algorithm. When we demand higher resolution for stationary target, it will cause blur with longer data acquisition time. Thus the application of the traditional imaging algorithm is limited. Compressed Sensing (CS) has recently attracted much interest as it can reduce the number of samples without compromising the imaging quality. Within this motivation, we discuss the applicability of CS and present the application constraint for HF radar system.