The Universal Lidar Error Model (Approved for Public Release: 15-144)

Abstract

AbstractMethods to adjust multiple lidar datasets, to adjust lidar with other modalities, and to quantify lidar accuracy are limited. While lidar sensor modeling, error propagation, and data adjustment exist in literature, there are no known implementations supporting all three operations within existing file formats and processing architectures. The Universal Lidar Error Model (ULEM) has been developed to meet the community-sneed for rigorous error propagation and data adjustment. ULEM exploitation allows one to develop predicted error covariance at single points and full covariance among multiple points. It defines a standardized set of adjustable parameters, provides for the modeling and storage of correlations and cross-correlations among parameters, and stores the data within existing file formats. This paper provides an introduction to ULEM, its metadata requirements, and its model exploitation methods. It concludes with an example of ULEM error modeling, showing the predicted uncertainty agrees well with errors calculated from surveyed control.