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Improving Low-Cost GNSS Navigation in Urban Areas by Integrating a Kinect Device

机译:通过整合Kinect设备,提高城市地区的低成本GNSS导航

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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.
机译:在过去的几十年中,低成本的GNSS接收器已被广泛用于导航目的。其中一些也提供了原始数据,允许更复杂的处理,例如双差异方法,因此更准确地定位,通常在排入级别。然而,这些准确性通常只能通过良好的天空能见度实现,即使使用配备有高敏感天线的低成本接收器,也是城市地区的一个关键问题。在这方面,从使用数字图像或致密点云的使用提供了重要贡献,这提供了对传感器运动位置的估计。为了维持低成本目标,可以使用赋予RGB和深度相机的Kinect装置。在这项工作中,我们首先通过使用自由和开源Gogps软件从U-Blox接收器处理GNSS原始数据。然后,我们研究了适当的卡尔曼滤波器通过适当的卡尔曼滤波器集成。户外实验已安排,目的是测试硬件和软件系统。

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