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Preliminary analysis of the RTK positioning using Android GNSS Raw Measurements and Application Feasibility for the Trajectory mapping using UAV's

机译:使用UAV的轨迹映射使用Android GNSS RAW测量和应用可行性初步分析

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With the release of Android N, Google announced the availability of GNSS Raw data from the mobile phone. This opens up to the broader prospective for research, analysis and enhancement of the positioning quality in mobile phones. With increasing applications based upon augmented reality, e-banking, e-health, etc., there is a rapid increase in the demand for precise positioning using the existing architecture of mobile devices. But, the quality of carrier phase raw data is not adequate for the substantial RTK (precise positioning). Artifacts in smartphone GNSS antenna, environmental degradation and cycle slips are few of the major issues to be addressed for reliable carrier phase positioning in the smartphone. The code range residual for kinematic and static measurement setup are very noisy in comparison to carrier phase residual. This results in invalid positioning solution with wrong ambiguity fixing. Doppler smoothed code pseudorange (Kalman Filter) shows a considerable improvement in the positioning accuracy as comparted to standard SPP solution. The RTK positioning is feasible with the raw GNSS data from the smartphone, but only float solutions are reliable. The position error due to gyroscope bias in x and y axis is 0.0036 m and 0.0032 m respectively and thus, can be used for small cycle slips detection and corrections.
机译:随着Android N的发布,Google宣布了来自手机的GNSS原始数据的可用性。这适用于更广泛的研究,分析和提高手机定位质量的前景。随着基于增强现实的增加,E-Banking,电子健康等,使用现有移动设备的架构对精确定位的需求快速增加。但是,载体阶段原始数据的质量不适用于大量RTK(精确定位)。智能手机GNSS天线的工件,环境退化和循环滑动是在智能手机中可靠的载波相位定位的主要问题中的一些主要问题。与载体相残差相比,运动学和静态测量设置的代码范围残差非常嘈杂。这导致无效的定位解决方案,具有错误的模糊固定。多普勒平滑码伪距(卡尔曼滤波器)显示了定位精度的相当大的改进,如图所示的定位精度为标准SPP解决方案。 RTK定位与来自智能手机的原始GNSS数据是可行的,但只有浮动解决方案可靠。由于X和Y轴的陀螺仪偏置引起的位置误差分别为0.0036 m和0.0032米,因此可用于小循环滑动检测和校正。

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