In the last decades, low-cost GNSS receivers have been widely used for navigation purposes. Some of them deliver also raw data, allowing for a more sophisticated processing, such as the double-difference approach, and therefore a more accurate positioning, typically at the decimeter level. However, these accuracies can be generally achieved only with a good sky visibility, that is a critical issue in urban areas even using low-cost receivers equipped with a high-sensitive antenna. In this respect, a significant contribution comes from the use of digital images or dense point clouds which provides an estimate of the sensor kinematic position. To maintain the low-cost target, the Kinect device, endowed with RGB and depth cameras, can be used. In this work, we have first processed the GNSS raw data from a u-blox receiver by using the free and open source goGPS software. Then, we have studied the integration of the Kinect device by a proper Kalman filter. An outdoor experiment has been arranged with the aim of testing the hardware and software system.

Improving low-cost GNSS navigation in urban areas by integrating a Kinect device

C. I. De Gaetani;D. Pagliari;M. Reguzzoni;L. Rossi;L. Pinto
2019

Abstract

In the last decades, low-cost GNSS receivers have been widely used for navigation purposes. Some of them deliver also raw data, allowing for a more sophisticated processing, such as the double-difference approach, and therefore a more accurate positioning, typically at the decimeter level. However, these accuracies can be generally achieved only with a good sky visibility, that is a critical issue in urban areas even using low-cost receivers equipped with a high-sensitive antenna. In this respect, a significant contribution comes from the use of digital images or dense point clouds which provides an estimate of the sensor kinematic position. To maintain the low-cost target, the Kinect device, endowed with RGB and depth cameras, can be used. In this work, we have first processed the GNSS raw data from a u-blox receiver by using the free and open source goGPS software. Then, we have studied the integration of the Kinect device by a proper Kalman filter. An outdoor experiment has been arranged with the aim of testing the hardware and software system.
International Symposium on Advancing Geodesy in a Changing World, Vol. 149, INTERNATIONAL ASSOCIATION OF GEODESY - ISSN: 0939-9585
978-3-030-12914-9
GNSS, Kalman filter, Kinect, Low-cost system, Multi-sensor navigation, Photogrammetry
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1078190
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