Proc. SPIE. 5808, Algorithms for Synthetic Aperture Radar Imagery XII
KEYWORDS: Signal to noise ratio, 3D acquisition, Detection and tracking algorithms, Data modeling, Synthetic aperture radar, Computer simulations, Clouds, 3D modeling, Device simulation, 3D image processing
Methods of generating more literal, easily interpretable imagery from 3-D SAR data are being studied to provide all weather, near-visual target identification and/or scene interpretation. One method of approaching this problem is to automatically generate shape-based geometric renderings from the SAR data. In this paper we describe the application of the Marching Tetrahedrons surface finding algorithm to 3-D SAR data. The Marching Tetrahedrons algorithm finds a surface through the 3-D data cube, which provides a recognizable representation of the target surface. This algorithm was applied to the public-release X-patch simulations of a backhoe, which provided densely sampled 3-D SAR data sets. The performance of the algorithm to noise and spatial resolution were explored. Surface renderings were readily recognizable over a range of spatial resolution, and maintained their fidelity even under relatively low Signal-to-Noise Ratio (SNR) conditions.