Kinematic surveying system for automatic GIS-data acquisition

Christian Hock; W. Caspary; H. Heister; J. Klemm; H. Sternberg

doi:10.1117/12.227858

1 December 1995 Kinematic surveying system for automatic GIS-data acquisition

Christian Hock, W. Caspary, H. Heister, J. Klemm, H. Sternberg

Proceedings Volume 2646, Digital Photogrammetry and Remote Sensing '95; (1995) https://doi.org/10.1117/12.227858
Event: Digital Photogrammetry and Remote Sensing '95, 1995, St. Petersburg, Russian Federation

Abstract

This paper deals with the design and development of a fast moving surveying system, which meets the demands of highest accuracy asked in geodesy and surveying for determining 3D- positions. The reader is introduced into real time capturing of GPS-, IMU- and CCD-camera outputsignals and into post-mission data processing for automatic digital information acquisition with the kinematic surveying system (KiSS). The absolute position of the moving vehicle within the global coordinate system (WGS84) is obtained by combining data from a GPS receiver and an inertial measuring unit (strapdown IMU). For compensating the errors of both sensors, additional sensing devices like odometer and barometer are utilized. Further improvement in position estimation is achieved by stereo photogrammetric measurements of known environmental objects, the so called landmarks. A digital stereo vision-system creates successive series of high resolution grayscale images, while a SVHS color video system records a continuous image sequence of the traveled road and the nearby surroundings. Depending on the demands of the application, selected environmental objects can be extracted, classified, and photogrammetrically positioned. THe parameters and the images of the acquired objects are indexed to the 3D-trajectory and saved in a GIS-database.

Citation Download Citation

Christian Hock, W. Caspary, H. Heister, J. Klemm, and H. Sternberg "Kinematic surveying system for automatic GIS-data acquisition", Proc. SPIE 2646, Digital Photogrammetry and Remote Sensing '95, (1 December 1995); https://doi.org/10.1117/12.227858

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