Abstract

The release of raw global navigation satellite system (GNSS) observations by Google Android makes high-precision positioning possible with low-cost smart devices. This study contributes to this research trend by constructing a stochastic model based on raw GNSS observation characteristics from Android smartphones and verifying the feasibility of smartphone-based ambiguity fixing in the short-baseline real-time kinematic (RTK) case. This study uses the raw observation standard deviations (ROSTDs) delivered by the Android application programming interface (API) as a stochastic model and takes advantage of the multipath index from the API to rule out unusable observations. As well as these, the ambiguity integer property is investigated by analyzing the residuals of double-differenced carrier-phase observations associated with one smartphone and one geodetic-grade receiver. Furthermore, we note that the carrier-phase observations collected by tested smartphones do not have the integer property but for the Huawei P30 and Xiaomi 8 devices, such an integer property can be successfully recovered by means of detrending. With the use of ROSTD-dependent weighting, we first perform single-point positioning (SPP) and real-time differentition (RTD) using pseudorange observations delivered by the Huawei P30 and Xiaomi 8 devices. The results show that the stochastic model is applicable to the Xiaomi 8. Moreover, the three-dimensional root-mean-square (3D-RMS) errors of the two smartphones for SPP are 1.28 m and 1.96 m, and the 3D-RMS errors for RTD are 0.79 m and 1.64 m, respectively. We next test the RTK positioning performance based on a short-baseline of 882 m using carrier-phase observations with recovered integer ambiguities. For the Huawei P30, the positioning errors achieved were 7.8, 2.4, 1.1 mm for the east, north, and up (ENU) components at the time of first fix while for the Xiaomi 8, the positioning errors achieved were 4.3, 4.2, 4.2 mm for the ENU components at the time of first fix.

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