A 2-D Image Stabilization Algorithm for UWB Pulse Radars with Fractional Boundary Scattering Transform

The UWB (ultra-wideband) pulse radar is a promising candidate as an environment measurement method for rescue robots. Radar imaging to locate a nearby target is known as an ill-posed inverse problem, on which various studies have been done. However, conventional algorithms require long computational time, which makes it difficult to apply them to real-time operations of robots. We have proposed a fast radar imaging algorithm, the SEABED algorithm, for UWB pulse radars. This algorithm is based on a reversible transform, BST (Boundary Scattering Transform), between the target shape and the observed data. This transform enables us to estimate target shapes quickly and accurately in a noiseless environment. However, in a noisy environment the image estimated by the SEABED algorithm is degraded because BST utilizes differential operations. We have also proposed an image stabilization method, which utilizes the upper bound of the smoothness of received data. This method can be applied only to convex objects, not to concave ones. In this paper, we propose a fractional BST, which is obtained by expanding the conventional BST, and an image stabilization method by using the fractional BST. We show that the estimated image can be stabilized regardless of the shape of target. key words: ultra-wideband (UWB) pulse radar, shape estimation, SEABED algorithm, boundary scattering transform (BST), stabilization, fractional BST (FBST)