Remote Sens. 2013, 5(11), 5805-5824; doi:10.3390/rs5115805
Article

Multi-Sensor Platform for Indoor Mobile Mapping: System Calibration and Using a Total Station for Indoor Applications

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Received: 10 September 2013; in revised form: 19 October 2013 / Accepted: 22 October 2013 / Published: 6 November 2013
(This article belongs to the Special Issue Advances in Mobile Laser Scanning and Mobile Mapping)
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Abstract: This paper addresses the calibration of mobile mapping systems and the feasibility of using a total station as a sensor for indoor mobile mapping systems. For this purpose, the measuring system of HafenCity University in Hamburg is presented and discussed. In the second part of the calibration, the entire system will be described regarding the interaction of laser scanners and other parts of the system. Finally, the preliminary analysis of the use of a total station is presented in conjunction with the measurement system. The difficulty of time synchronization is also discussed. In multiple tests, a comparison was made versus a reference solution based on GNSS. Additionally, the suitability of the total station was also considered for indoor applications.
Keywords: calibration; total station; Kalman filter; inertial navigation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Keller, F.; Sternberg, H. Multi-Sensor Platform for Indoor Mobile Mapping: System Calibration and Using a Total Station for Indoor Applications. Remote Sens. 2013, 5, 5805-5824.

AMA Style

Keller F, Sternberg H. Multi-Sensor Platform for Indoor Mobile Mapping: System Calibration and Using a Total Station for Indoor Applications. Remote Sensing. 2013; 5(11):5805-5824.

Chicago/Turabian Style

Keller, Friedrich; Sternberg, Harald. 2013. "Multi-Sensor Platform for Indoor Mobile Mapping: System Calibration and Using a Total Station for Indoor Applications." Remote Sens. 5, no. 11: 5805-5824.


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