Abstract

The release of raw Android global navigation satellite system (GNSS) measurements makes high-precision positioning achievable with low-cost smart devices. Affected by low-cost GNSS chips, linearly polarized antennas, and complex observation environments, Android GNSS observations usually contain a large number of outliers, which significantly degrade their positioning precision and reliability. To address this issue, a robust real-time kinematic (RTK) scheme with sliding window-based factor graph optimization (FGO) was developed. The scheme adopts the GNSS carrier-phase sliding window marginalization, models the carrier-phase ambiguity as a random constant, and incorporates multiple robust estimation strategies. Vehicle kinematic positioning validations were carried out in both open-sky and complex urban environments using representative Xiaomi Mi8 and Huawei P40 smartphones. Using the proposed scheme, the root mean square (rms) of the positioning errors in the east, north, and up components in the open-sky environments is 0.18, 0.13, and 0.38 m, respectively. In complex urban environments, the rms of the positioning precisions in the east, north, and up components was as decent as 1.42, 1.97, and 2.63 m, respectively.

Full Text
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