Ultra wideband (UWB) radar is considered a promising technology to complement existing camera-based surveillance systems because, unlike cameras, it provides excellent range resolution. Many of the UWB radar imaging algorithms are based on large-scale antenna arrays that are not necessarily practical because of their complexity and high cost. To resolve this issue, we previously developed a two-dimensional radar imaging algorithm that estimates unknown target shapes and motion using only three antennas. In this paper, we extend this method to obtain three-dimensional images by estimating three-dimensional motions from the outputs of five antennas. Numerical simulations confirm that the proposed method can estimate accurately the target shape under various conditions.

UWB (ultra wide-band) pulse radar is a promising candidate for surveillance systems. The fast SEABED (Shape Estimation Algorithm based on BST and Extraction of Directly scattered waves) imaging algorithm is deployed in the application of UWB pulse radar in fields that require real-time operations. However, since the SEABED algorithm uses signals received at multiple locations, this method either needs to scan antennas or to install many antennas. Such systems are inevitably costly and unrealistic for applications such as surveillance. To overcome this problem, a revised SEABED algorithm that estimates unknown target shape based on target motion using only a pair of fixed antennas was developed. However, the method cannot be used when the target moves arbitrarily because it assumes the target motion is parallel to the baseline of the pair of antennas. In this paper, we propose a new UWB radar imaging algorithm that is applicable even for targets with arbitrary motion. The proposed method introduces another antenna which is added to the pair of antennas used in the revised SEABED, and estimates unknown target motion based on the target surface using the three antennas. Next, the proposed method applies the SEABED imaging algorithm to the estimated motion and obtains the target image. Some numerical simulations establishes that the proposed method can accurately estimate the target shape even under severe conditions.