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Emulating the Smartphone GNSS Receiver to Understand and Analyze the Anomalies in RTK Positioning using GNSS Raw Measurements

机译:使用GNSS RAW测量模拟智能手机GNSS接收器以了解并分析RTK定位中的异常

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With the release of Android N, Google announced the availability of GNSS Raw data from the mobile phone. This opens a broader perspective 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. On one hand, error sources such as ionospheric error and multipath mitigation tend to degrade the quality of precise positioning in mobile phones. On the other hand, cycle slip introduced due to weaker carrier-phase signal makes the positioning in mobile phone code-phase dependent only. Now with the availability of GNSS raw data, researchers are getting the opportunity to analyze and develop new concepts to enhance the carrier-phase positioning into a mobile phone. The approach presented in this paper is to emulate the smartphone and understand the effect of inducing noise in Pseudorange and Carrier phase artificially. The GNSS data recorded from smartphone directly cannot be manipulated to analyze the role of e.g. cycle slip in positioning accuracy quantitatively. Secondly, due to the hardware limitation, tracking inside the smartphone cannot be controlled which makes it difficult for researchers to play round with the GNSS data. Based upon the statistical analysis performed on the code and carrier residual from the smartphone, a high quality GNSS data was degraded. Results presented in the paper clearly indicates that the degradation of positioning accuracy due to the presence of noise introduced in the Carrier phase and Pseudorange. The first section gives user an understanding with state of the art positioning technique which is currently used in smartphones. Section 2 will give detailed description about data logging setup and techniques for inducing artifacts for emulating smartphone. In the following section results and analysis with different scenarios are discussed. In the final section paper will conclude the future possibilities and the extension of the work.
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。这为移动电话中的定位质量进行了更广泛的研究,分析和提高了更广泛的视角。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。一方面,诸如电离层误差和多路径缓解的误差源往往会降低移动电话中精确定位的质量。另一方面,由于较弱的载波相位信号引入的循环滑移仅在移动电话码相中取决于移动电话代码相位。现在通过GNSS原始数据的可用性,研究人员正在有机会分析和开发新概念,以增强运营商定位到移动电话中。本文呈现的方法是模拟智能手机,并了解人为地诱导噪声噪声的噪声。从智能手机记录的GNSS数据直接无法操纵以分析例如智能作用。定量定量精度循环滑动。其次,由于硬件限制,无法控制智能手机内部的跟踪,这使得研究人员难以使用GNSS数据来玩。基于对智能手机的代码和载波剩余的统计分析,高质量的GNSS数据劣化。本文中提出的结果清楚地表明由于载体相位和伪橙色引入的噪声存在,定位精度的降低。第一部分为用户提供了与当前用于智能手机中使用的技术定位技术的理解。第2节将详细说明数据记录设置和用于诱导模拟智能手机的工件的技术。在以下部分中,讨论了不同场景的结果和分析。在最后一节文件中,将缔结未来的可能性和延伸工作。

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