Microwave And Video Sensor Fusion For The Shape Extraction Of 3D Space Objects

摘要

In order for robots to perform meaningful operations in space, some type of sophisticated vision system is required. Such a system should provide the robot with three dimensional (3D) information about its surrounding work space and the objects to be operated on. The problem of remotely determining an object's 3D shape is difficult in any situation, but the space environment presents special problems due to the ambient illumination and lack of atmosphere. The most common imaging systems, visual sensors, are able to accurately determine the boundary of an object's two-dimensional projection onto the image plane. The exact shape of an object can be determined through the analysis of shading in an optical image, but frequently, shading details are obscured by the high intensity specular reflections which occur in space images. An alternate sensor for robotic applications is microwave radar. Some 3D information is available from time-domain radar imaging, but high resolution radar is prohibitively expensive and complex. We would like to integrate the information available from T .V . images and low-resolution radar scattering cross-sections to reconstruct an object's 3D shape. We present a new system for the fusion of optical image data and polarized radar scattering cross-sections. The radar data is used in an iterative procedure which generates successive approximations to the target shape by minimizing the error between the computed scattering cross-sections, and the observed radar returns. The image data is incorporated by supplying an initial estimate of shape through knowledge of the two-dimensional silhouette and shading models. These components are assembled into a larger iterative process designed to refine the estimate of 3D shape and obtain the best possible description of the attitude and motion of the target.