3-D Point Cloud Generation From Airborne Single-Pass and Single-Channel Circular SAR Data

Abstract

This article presents a framework to generate 3-D point clouds by very-high-resolution single-pass and single-channel circular synthetic aperture radar (CSAR). The focus is both on the precise 3-D determination of very small, detached objects and on larger buildings in complex urban scenes. Inspired by optical flow methods, our approach evaluates the tracked aspect dependent backscatter energy flow of objects above the focusing reference plane. Besides the derivation of the exact projection geometry in CSAR, we give answers to the question of how accurate 3-D information can be extracted by this approach as a function of aspect interval and the object’s signal-to-clutter ratio (SCR). A further coherent adaption uses considerably larger subapertures while focusing the data on different reference heights. The computed 3-D information from multiple aspect views is then fused to a georeferenced 3-D point cloud. This results in the first demonstration of 3-D point cloud generation from CSAR data collected with a frequency-modulated continuous-wave (FMCW) radar at the W-band. The results were validated with light detection and ranging (LiDAR) data, and the height accuracy was evaluated in relation to the aspect integration interval and the number of aspect views. For small point targets with edge lengths of 3 cm, we could demonstrate that an aspect interval of only 8.5° leads to a height accuracy below 20 cm. Building roofs reach a height accuracy of several tens of centimeters. Besides the spatial information, we can reveal the angular scattering behavior of individual objects and determine over which aspect interval they are even visible.