[G05-P] Poster

[G05-P-03] Improving low-cost GNSS navigation in urban areas using multi-constellation receivers and integrating a Kinect device

Diana Pagliari¹, Carlo Iapige De Gaetani¹, Eugenio Realini², Mirko Reguzzoni^1,2, Lorenzo Rossi¹, Livio Pinto¹, ^○Riccardo Barzaghi¹ (1.Department of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy, 2.GReD srl, Lomazzo (CO), Italy)

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 multi-constellation signal that increases the number of visible satellites. An additional possibility is the integration of the GNSS receiver with a camera or a laser scanner. In fact, the external orientation of the acquired digital images or dense point clouds ultimately provides an estimate of the sensor kinematic position.
In this work, we have first studied the contribution of the different GNSS constellations to the accuracy and the temporal continuity of the estimated trajectory in outdoor urban environment by a low-cost receiver, such as u-blox or NVS devices. The free and open source goGPS software has been used to process the receiver raw data. Then, we have studied the integration of the Kinect device into the navigation system. This device is endowed with a depth camera, as well as a RGB camera, at a cost of about 200$, thus maintaining our main target of realizing a low-cost system. A proper Kalman filter has been implemented for jointly processing the GNSS estimated coordinates and the images of the Kinect cameras. An outdoor experiment has been arranged with the aim of testing the hardware and software system. The results show that the obtained improvement is more significant for the temporal continuity of the trajectory rather than for its accuracy.