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Statistical Investigation of Android GNSS Data: Case Study Using Xiaomi Mi 8 Dual-Frequency Raw Measurements

机译:Android GNSS数据的统计调查:案例研究采用XIAMI MI 8双频原料测量

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Officially released on August 2016, the Android 7.0 has been a breakthrough for the Global Navigation Satellite System (GNSS) community. Starting with the introduction of its Application Programming Interface 24 (API 24), Android users have been able to directly access raw GNSS measurements within their smartphone, independently on the specific phone design or manufacturer. In this research we consider as a case-study device the Xiaomi Mi 8, equipped with the BCM47755 location hub (first dual-frequency GNSS chipset), after being upgrade to Android 9.0 in order to access new functionalities implemented in the API 28. The analysis of raw measurements and their quality is fundamental in smartphone-based positioning, since biased or extremely noisy estimates of the pseudorange measurements will hamper the precise positioning performances. Here, we report on several tests performed in static mode over a geodetic pillar, under similar conditions and covering time-spans up to several hours. Main quantities retrieved from the API were first described and then characterized based on the statistics retrieved from all these long dataset. After some considerations, a dependency w.r.t. the carrier-to-noise density ratio (C/N0) has been investigated for some of these variables, as well as for the impact of the API multipath indicator on the available observations. Finally, a preliminary C/N0-based trade-off between data 'quantity' and ‘quality’ is here proposed in order to support smartphone-based precise positioning.
机译:Android 7.0在2016年8月正式发布,这是全球导航卫星系统(GNSS)社区的突破。从引入其应用程序编程界面24(API 24)开始,Android用户能够独立于特定电话设计或制造商直接在其智能手机内访问原始GNSS测量。在本研究中,我们认为作为一个案例研究设备,小MI 8,配备了BCM4755位置集线器(第一个双频GNSS芯片组),升级到Android 9.0以便访问API 28中实现的新功能。该原始测量分析及其质量是基于智能手机的定位的基础,因为伪距测量的偏差或极度嘈杂的估计将妨碍精确定位性能。在这里,我们在类似条件下,在大地柱上以静态模式进行的几次测试报告,并且覆盖时间跨越几个小时。首先描述从API检索的主数量,然后基于从所有这些长数据集中检索的统计信息来表征。经过一些考虑因素,一个依赖性w.r.t.已经研究了载波噪声密度比(C / N0)对于这些变量中的一些,以及API多径指标对可用观察的影响。最后,提出了数据“数量”和“质量”之间的初步C / N0的权衡,以支持基于智能手机的精确定位。

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