On the Path to Precision - Observations with Android GNSS Observables

Riley, Stuart; Lentz, W. Mac; Clare, Adam

doi:10.33012/2017.15244

Cited by 37 publications

(32 citation statements)

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“…For GPS, where only the fractional part of the double differences is presented, ideally, it would be expected that these would be close to a constant function at zero if the doubledifferenced phase ambiguities are assumed to be integers. It has, however, been demonstrated by Realini et al (2017) and Riley et al (2017) that double-differenced phase ambiguities of Nexus 9 measurements are not of integer nature. These results are also confirmed in this study.…”

Section: Assessment Of the Phase Observationsmentioning

confidence: 99%

“…Actual accuracies could not be determined as the true position of the device was unknown. Riley et al (2017) at Trimble assessed precise positioning for several Android devices, including Samsung Galaxy S7 and the Nexus 9 tablet. Precise positions were determined both with real-time kinematic (RTK) positioning and with pseudorange and Doppler only.…”

Section: Introductionmentioning

confidence: 99%

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Characterization of GNSS observations from a Nexus 9 Android tablet

Håkansson

2018

GPS Solut

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Global navigation satellite system (GNSS) raw data were made available in the application programming interface (API) starting from version 7.0 of the Android operating system. This opens possibilities for precise positioning with Android devices, as externally generated GNSS corrections can now be included in the positioning estimation in a convenient way. The Nexus 9 tablet is a good candidate for an early assessment of the raw GNSS observables and the corresponding derived precise positions, as it also supports many of the optional features and observation types presented by the API, including carrier phase observations which play an important role in many precise positioning techniques. It is known from the previous studies that poor handling of multipath in smartphones and tablets is a big challenge when it comes to precise GNSS positioning with these kinds of devices. Hence, this study assesses the raw GNSS observations and the calculated precise positions of the Nexus 9 tablet in two experimental setups with different multipath impacts. In addition, various biases of the observations are determined, some of which is not present on high-grade geodetic receivers. The analysis is done for GPS and GLONASS, which are supported by the Nexus 9 tablet. The study shows that multipath plays an important role for the expected accuracy of the calculated precise positions, both due to the induced error on the measurements, and due to loss of lock of the GNSS signals, which significantly affects precise positioning from carrier-phase measurements. Position accuracy ranges from just below 1 m to a few decimeters between the experimental setups with moderate and low levels of multipath respectively, for positioning based on carrier-phase observations. It is, furthermore, demonstrated that consideration of code inter-system biases and code inter-frequency biases of the Nexus 9 tablet are crucial for differential GNSS with multiple GNSS systems and when GLONASS observations are used in the positioning solutions. Besides these expected biases, also other less expected behaviors were discovered in the Nexus 9 GNSS observations, including various drifts for the code and phase observations. This study also proposes some strategies to handle these.

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Section: Assessment Of the Phase Observationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Characterization of GNSS observations from a Nexus 9 Android tablet

Håkansson

2018

GPS Solut

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“…Android smartphones that can record raw GNSS pseudorange (and most recently carrier phase) measurements have been available since late 2016 and initial results have shown promising potential for positioning (e.g., [1,2]). Since a main purpose of a smartphone is communication, the GNSS capability comes at limited additional expense.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a Low Cost Hand Held Unit with GNSS Raw Data Capability and Comparison with an Android Smartphone

Gratton

Horrelt

Lemieux

et al. 2018

Sensors

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A newly available portable unit with GNSS raw data recording capability is assessed to determine static and kinematic position accuracy in various environments. This unit is the GPSMap 66, introduced by Garmin in early September. It is all-weather and robust for field use, and comes with a helix antenna. The high sensitivity chipset is capable of acquiring and tracking signals in highly attenuated environments. It can track single frequency GPS, GPS + GLONASS or GPS + Galileo and record code, Doppler and carrier phase data every second in the RINEX format. The evaluation presented herein focusses on GPS and Galileo. Static and kinematic test results obtained under a wide range of realistic field conditions are reported. Differential GNSS methods and Precise Point Positioning (PPP) are used to assess absolute position accuracy in ITRF coordinates, which is sufficiently close to the GPS and Galileo reference frame for the current purpose. Under low multipath conditions, measurements are found to be sufficiently accurate to provide single epoch, bias free position accuracy of a few metres. Accuracy is a function of signal attenuation and multipath conditions. The use of an external geodetic antenna significantly reduces measurement noise and multipath in high multipath environments. Carrier phase measurements, available more or less continuously under open sky conditions, significantly improve performance in differential mode. Accuracy in vehicular mode using code and carrier phase differential RTK solution is at the level of a few to several dm. Tests were conducted in parallel with a Huawei P10 Android 8.0 smartphone. The code measurement noise of this unit was found to be significantly higher than that of the GPSMap 66, a major reason being its lower performance PIFA antenna; carrier phase was only available for short time intervals, significantly degrading differential position accuracy performance.

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“…These varying biases of the code observables are also referred to as group delay variations (GDV).Previous studies by Wanninger and Beer [11] and Wanninger, Sumaya, and Beer [12] have shown that nadir-dependent GDV affect precise point positioning (PPP) based on the single frequency ionosphere-free combination, wide-lane ambiguity fixing based on the Hatch-Melbourne-Wübbena linear combination [13][14][15], as well as TEC estimation of the ionosphere. The latter is an important characteristic of the ionosphere and is necessary in some single frequency precise positioning applications, for instance, precise positioning with mobile devices, which has gained significant attention in recent years [16][17][18][19][20][21][22][23][24][25][26][27]. For the verification and further understanding of these effects, the independent evaluation of previously used methods is therefore important.In this study, we investigated how nadir-dependent GDV affect ionosphere modeling by analyzing the model residuals that they give rise to.…”

mentioning

confidence: 99%

Nadir-Dependent GNSS Code Biases and Their Effect on 2D and 3D Ionosphere Modeling

Håkansson

2020

Remote Sensing

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Recent publications have shown that group delay variations are present in the code observables of the BeiDou system, as well as to a lesser degree in the code observables of the global positioning system (GPS). These variations could potentially affect precise point positioning, integer ambiguity resolution by the Hatch-Melbourne-Wübbena linear combination, and total electron content estimation for ionosphere modeling from global navigation satellite system (GNSS) observations. The latter is an important characteristic of the ionosphere and a prerequisite in some applications of precise positioning. By analyzing the residuals from total electron content estimation, the existence of group delay variations was confirmed by a method independent of the methods previously used. It also provides knowledge of the effects of group delay variations on ionosphere modeling. These biases were confirmed both for two-dimensional ionosphere modeling by the thin shell model, as well as for three-dimensional ionosphere modeling using tomographic inversion. BeiDou group delay variations were prominent and consistent in the residuals for both the two-dimensional and three-dimensional case of ionosphere modeling, while GPS group delay variations were smaller and could not be confirmed due to the accuracy limitations of the ionospheric models. Group delay variations were, to a larger extent, absorbed by the ionospheric model when three-dimensional ionospheric tomography was performed in comparison with two-dimensional modeling.computerized ionospheric tomography (CIT) [2][3][4], techniques that were inspired by and have emerged from computerized tomography (CT) for medical applications [5].GNSS hardware biases [6], and especially biases in the code observations, are well-known to affect the estimation of TEC from GNSS observations [7][8][9]. These biases, referred to as differential code biases (DCBs), are regarded as constant offsets between code observations associated with two signals transmitted between the same satellite and receiver. Thereby, an offset exists in addition to the expected offset due to different ionospheric influence caused by the difference in carrier frequencies. However, even though these biases have been assumed to be constant, recent findings by Hauschild et al. [10], Wanninger and Beer [11], and Wanninger et al. [12] show that the code biases also have a nadir-dependent component, with the largest effects shown for BeiDou [11], but with measurable effects also shown for other GNSSs [12]. These varying biases of the code observables are also referred to as group delay variations (GDV).Previous studies by Wanninger and Beer [11] and Wanninger, Sumaya, and Beer [12] have shown that nadir-dependent GDV affect precise point positioning (PPP) based on the single frequency ionosphere-free combination, wide-lane ambiguity fixing based on the Hatch-Melbourne-Wübbena linear combination [13][14][15], as well as TEC estimation of the ionosphere. The latter is an important characteristic of the ionosphere and is necess...

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On the Path to Precision - Observations with Android GNSS Observables

Cited by 37 publications

References 0 publications

Characterization of GNSS observations from a Nexus 9 Android tablet

Characterization of GNSS observations from a Nexus 9 Android tablet

Evaluation of a Low Cost Hand Held Unit with GNSS Raw Data Capability and Comparison with an Android Smartphone

Nadir-Dependent GNSS Code Biases and Their Effect on 2D and 3D Ionosphere Modeling

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