CMRT09

Stilla, Uwe

Bibliographic data

Monograph

Persistent identifier:: 856955019

Author:: Stilla, Uwe

Title:: CMRT09

Sub title:: object extraction for 3D city models, road databases, and traffic monitoring ; concepts, algorithms and evaluation ; Paris, France, September 3 - 4, 2009 ; [joint conference of ISPRS working groups III/4 and III/5]

Scope:: X, 234 Seiten

Year of publication:: 2009

Place of publication:: Lemmer

Publisher of the original:: GITC

Identifier (digital):: 856955019

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: UTILIZATION OF 3D CITY MODELS AND AIRBORNE LASER SCANNING FOR TERRAIN-BASED NAVIGATION OF HELICOPTERS AND UAVs M. Hebel, M. Arens, U. Stilla

Document type:: Monograph

Structure type:: Chapter

In: Stilla U, Rottensteiner F, Paparoditis N (Eds) CMRT09. IAPRS, Voi. XXXVIII, Part 3/W4 — Paris, France, 3-4 September, 2009 UTILIZATION OF 3D CITY MODELS AND AIRBORNE LASER SCANNING FOR TERRAIN-BASED NAVIGATION OF HELICOPTERS AND UAVs M. Hebel a , M. Arens a , U. Stilla b a FGAN-FOM, Research Institute for Optronics and Pattern Recognition, 76275 Ettlingen, Gennany - hebel@fom.fgan.de b Photogrammetry and Remote Sensing, Technische Universität München, 80290 München, Gennany - stilla@bv.tum.de KEY WORDS: Airborne laser scanning, LiDAR, GPS/INS, on-line processing, navigation, city models, urban data ABSTRACT: Airborne laser scanning (ALS) of urban regions is commonly used as a basis for 3D city modeling. In this process, data acquisition relies highly on the quality of GPS/INS positioning techniques. Typically, the use of differential GPS and high-precision GPS/INS postprocessing methods are essential to achieve the required accuracy that leads to a consistent database. Contrary to that approach, we aim at using an existing georeferenced city model to correct errors of the assumed sensor position, which is measured under non differential GPS and/or INS drift conditions. Our approach accounts for guidance of helicopters or UAVs over known urban terrain even at night and during frequent loss of GPS signals. We discuss several possible sources of errors in airborne laser scanner systems and their influence on the measured data. A workflow of real-time capable methods for the segmentation of planar surfaces within ALS data is described. Matching planar objects, identified in both the on-line segmentation results and the existing city model, are used to correct absolute errors of the sensor position. 1. INTRODUCTION 1.1 Problem description Airborne laser scanning usually combines a LiDAR device (light detection and ranging) with high-precision navigational sensors (INS and differential GPS) mounted on an aircraft. Range values are derived from measuring the time-of-flight of single laser pulses, and scanning is performed by one or more deflection mirrors in combination with the forward moving aircraft. The navigational sensors are used to obtain the 3D point associated with each range measurement, resulting in a georeferenced point cloud of the terrain. A good overview and a thorough description of ALS principles can be found in (Wehr & Lohr, 1999). Laser scanning delivers direct 3D measurements independently from natural lighting conditions, and it offers high accuracy and point density. A well-established application of laser point clouds acquired at urban areas is the generation of 3D city models. However, the overall precision of the derived city model highly depends on the accuracy of the data input, which is directly dependent on the exactitude of the navigational information. Great efforts are usually required during data acquisition and postprocessing in order to achieve high fitting accuracy of multiple ALS datasets (e.g. neighboring strips). While ALS data acquisition is commonly done to supply other fields of studies with the necessary data, few examples can be found where laser scanners are used directly for pilot assistance. One of these examples is the HELLAS obstacle warning system for helicopters (Schulz et al., 2002), which is designed to detect wires and other obstacles for increased safety during helicopter missions. Despite increasing performance of LiDAR systems, most remote sensing tasks that require on-line data processing are still accomplished by the use of conventional CCD or infrared cameras. Typical examples are airborne monitoring and observation devices that are used for automatic object recognition, situation analysis or real-time change detection. Utilization of these sensors can support law enforcement, firefighting, disaster management, and medical or other emergency services. At the same time, it is often desirable to assist pilots with obstacle avoidance and aircraft guidance in case of poor visibility conditions, during landing operations, or in the event of GPS dropouts. Three-dimensional information as provided by the LiDAR sensor technology can ease these tasks, but the existence of differential GPS ground stations and the feasibility of comprehensive data analysis are not to be considered for these real-time operations. 1.2 Overview The approach of using ALS information to provide on-line navigation support for aircraft guidance over urban terrain is opposite to the process of city model generation. In contrast to the demand for high-precision positioning techniques, it is assumed that a proper georeferenced city model is already available. This database can be used to generate a synthetic vision of the terrain according to current position and orientation of the aircraft. Moreover, ALS measurements and matching counterparts in the city model can be taken into consideration if additional navigational information is needed, for example in cases of degraded GPS positioning accuracy. This paper presents a workflow of methods for the segmentation of planar surfaces in ALS data that can be accomplished in line with the data acquisition process. Since most of currently used airborne laser scanners, like the RIEGL LMS-Q560, measure range values in a pattern of parallel scan lines, the analysis of geometric features is performed directly on this scan line data. Straight line segments are first segmented and then connected across consecutive scan lines to result in planar surfaces. All proposed operations are applicable for on-line data processing.

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