Radar array self-calibration and imaging with applications to bulk material gauging

Common algorithms for radar array imaging rely on sufficiently precise calibration before evaluation. A system calibration is necessary to compensate potential unavoidable error sources that decrease the accuracy and reliability of the estimates and worsen the beam pattern of the antenna array. Several calibration methods have been developed, most of them are based on a-priori, i.e., offline measurements with a well defined target scenario. In this paper we present an algorithm that is capable of executing an online self-calibration and image formation for the special case when the target scenario is an arbitrary but continuous surface. The two separated tasks, system calibration followed by image formation, are combined in a single formulation that efficiently solves a minimization problem. Thus, the need for a-priori calibration measurements is avoided. The correct functionality of this algorithm is shown with simulation results for different surface scenarios and spatial dimensions. A possible real-world application in blast furnace burden surface imaging is discussed.