Dokument-ID Dokumenttyp Autoren/innen Persönliche Herausgeber/innen Haupttitel Abstract Auflage Verlagsort Verlag Herausgeber (Institution) Erscheinungsjahr Titel des übergeordneten Werkes Jahrgang/Band ISBN Veranstaltung Veranstaltungsort Beginndatum der Veranstaltung Enddatum der Veranstaltung Ausgabe/Heft Erste Seite Letzte Seite URN DOI Lizenz Datum der Freischaltung OPUS4-26028 Beitrag zu einem Tagungsband Köppe, Enrico; Bartholmai, Matthias; Liers, A.; Schiller, J. Radio-based multi-sensor system for person tracking and indoor positioning Sensor based person tracking is a challenging topic. The main objective is positioning in areas without GPS connection, i.e. indoors. A research project is carried out at BAM, Federal Institute for Materials Research and Testing, to develop and to validate a multi-sensor system for 3D localization. It combines body motion sensing and a guard system for the tracking and recording of the status of persons. The so named BodyGuard system was designed for sensor-based monitoring and radio-based transmission of the movement of a person. Algorithms were developed to transform the sensor data into a spatial coordinate. This paper describes how the BodyGuard system operates, which main components were used in the system, how the individual sensor data are converted into 3D motion data, with which algorithms the individual sensors are processed, how individual errors are compensated and how the sensor data are merged into a 3D Model. Final objective of the BodyGuard system is to determine the exact location of a person in a building, e.g. during fire-fighting operations. Dresden Hochschule für Technik und Wirtschaft Dresden 2012 WPNC 2012 - 9th Workshop on positioning, navigation and communication WPNC '12 - 9th Workshop on positioning, navigation and communication 2012 Dresden, Germany 2012-03-15 2012-03-16 PS 11 1 7 2016-02-19 OPUS4-24402 Beitrag zu einem Tagungsband Köppe, Enrico; Bartholmai, Matthias; Liers, A.; Schiller, J. Tracking persons using a radio-based multi-sensor system A multi-sensor system for 3D localization was developed and named BodyGuard. It combines body movement sensing and a guard system for the tracking and recording of the status of persons. BodyGuard was designed to monitor and transmit the movement of a person radio-based and to transform that data into a spatial coordinate. This paper describes how the BodyGuard system works, what components the system consists of, how the individual sensor data is converted into 3D motion data, with which algorithms the individual sensors are processed, how individual errors are compensated and how the sensor data are fused into a 3D Model. 2011 IPIN 2011 - International conference on indoor positioning and indoor navigation IPIN 2011 - International conference on indoor positioning and indoor navigation Guimaraes, Portugal 21.09.2011 23.09.2011 1 4 2016-02-19 OPUS4-32645 Beitrag zu einem Tagungsband Köppe, Enrico; Augustin, D.; Liers, A.; Schiller, J. Enhancement of the automatic 3D calibration for a multi-sensor system The calibration of the integrated sensors in a multisensor system has gained in interest over the last years. In this paper we introduce an enhanced calibration process, which is based on the preceding study described in. The enhancement consists of the integration of a gyroscope. So far only the accelerometer and the magnetic field sensor were taken into account for the calibration process. Due to this improvement we reach a better approximation of the accelerometer and the magnetic field sensor. Additionally, we minimize the standard deviation of the single sensors and improve the accuracy of the positioning of a moving person. 2013 IPIN 2013 - 4th International conference on indoor positioning and indoor navigation 978-1-4799-4043-1 IPIN 2013 - 4th International conference on indoor positioning and indoor navigation Belfort-Montbéliard, France 28.10.2013 31.10.2013 11 13 2016-02-20 OPUS4-32428 Beitrag zu einem Tagungsband Köppe, Enrico; Augustin, D.; Liers, A.; Schiller, J. Self-calibration-method for an inertial navigation system with three 3D sensors Inertial Navigation Systems with three 3D sensors are used to localize moving persons. The accuracy of the localization depends on the quality of the sensor data of the multi-sensor system. In order to improve the accuracy, a self-calibration process based on the automatic 3D calibration was developed. Based on the calibration procedure of the accelerometer (ACC) and the magnetic field sensor (MAG), the additional integration of the gyroscope (GYRO) leads to a reduction of the indoor positioning error. This improves both the approximation for the accelerometer and the magnetic field sensor so that the standard deviation of a single sensor is minimized. A new calibration procedure of the gyroscope and the accuracy improvement of the localization of a moving person are presented. Institute of Electrical and Electronics Engineers (IEEE) 2014 ISISS 2014 - 1st IEEE International Symposium on Inertial Sensors and Systems (Proceedings) 978-1-4799-0915-5 ISISS 2014 - 1st IEEE International Symposium on Inertial Sensors and Systems Laguna Beach, CA, USA 25.02.2014 26.02.2014 93 96 10.1109/ISISS.2014.6782522 2016-02-20 OPUS4-32430 Beitrag zu einem Sammelband Köppe, Enrico; Augustin, D.; Köppe, Tabea; Subaric-Leitis, Andreas; Liers, A.; Schiller, J. Gartner, G.; Huang, H. Application of the inertial navigation system 3D-self-calibration-method for the minimization of the measurement uncertainty For the accuracy of inertial navigation systems for indoor localization it is important to get high quality sensor data of the multi-sensor system. This can be realized using high quality sensors or the developed 3D-self-calibration-method for low cost sensors. Based on the calibration procedure of the accelerometer (ACC) and the magnetic field sensor (MAG), the additional integration of the gyroscope (GYRO) leads to a reduction of the indoor positioning error. This improves both the approximation for the accelerometer, the magnetic field sensor and the gyroscope so that the standard deviation of a single sensor is minimized. There are errors in the whole system. To determine these error sources it is important to define the measurement uncertainty. In this paper it is presented that the measurement uncertainty can be reduced by the application of the developed 3D-self-calibration method. Springer 2014 Progress in location - based services 2014 978-3-319-11878-9 11th International Symposium on Location Based Services Vienna, Austria 26.11. 2014 28.11.2014 105 117 10.1007/978-3-319-11879-6_8 2016-02-20