Precise Point Positioning (PPP) with Ambiguity Resolution (AR) is an important high-precision positioning technique that is gaining popularity in geodetic and geophysical applications. The implementation of PPP-AR requires precise products such as orbits, clocks, code, and phase biases. As one of the analysis centers of the International Global Navigation Satellite System (GNSS) Service (IGS), the Wuhan University Multi-GNSS experiment (WUM) Analysis Center (AC) has provided multi-GNSS Observable-Specific Bias (OSB) products with the associated orbit and clock products. In this article, we first introduce the models and generation strategies of WUM rapid phase clock/bias products and orbit-related products (with a latency of less than 16 h). Then, we assess the performance of these products by comparing them with those of other ACs and by testing the PPP-AR positioning precision, using data from Day of the Year (DOY) 047 to DOY 078 in 2022. It is found that the peak-to-peak value of phase OSBs is within 2 ns, and their fluctuations are caused by the clock day boundary discontinuities. The associated Global Positioning System (GPS) orbits have the best consistency with European Space Agency (ESA) products, and those of other systems rank in the medium place. GLObal NAvigation Satellite System (GLONASS) clocks show slightly inconsistency with other ACs’ due to the antenna thrust power adopted, while the phase clocks of other GNSSs show no distortion compared with legacy clocks. With well-estimated phase products for Precise Orbit Determination (POD), the intrinsic precision is improved by 14%, 17%, and 24% for GPS, Galileo navigation satellite system (Galileo), and BeiDou-3 Navigation Satellite System (BDS-3), respectively. The root mean square of PPP-AR using our products in static mode with respect to IGS weekly solutions can reach 0.16 cm, 0.16 cm, and 0.44 cm in the east, north, and up directions, respectively. The multi-GNSS wide-lane ambiguity fixing rates are all above 90%, while the narrow-lane fixing rates above 80%. In conclusion, the phase OSB products at WUM have good precision and performance, which will benefit multi-GNSS PPP-AR and POD.

In May 2016, the availability of GNSS raw measurements on smart devices was announced by Google with the release of Android 7. It means that developers can access carrier-phase and pseudorange measurements and decode navigation messages for the first time from mass-market Android-devices. In this paper, an improved Hatch filter algorithm, i.e., Three-Thresholds and Single-Difference Hatch filter (TT-SD Hatch filter), is proposed for sub-meter single point positioning with raw GNSS measurements on Android devices without any augmentation correction input, where the carrier-phase smoothed pseudorange window width adaptively varies according to the three-threshold detection for ionospheric cumulative errors, cycle slips and outliers. In the mean time, it can also eliminate the inconsistency of receiver clock bias between pseudorange and carrier-phase by inter-satellite difference. To eliminate the effects of frequent smoothing window resets, we combine TT-SD Hatch filter and Kalman filter for both time update and measurement update. The feasibility of the improved TT-SD Hatch filter method is then verified using static and kinematic experiments with a Nexus 9 Android tablet. The result of the static experiment demonstrates that the position RMS of TT-SD Hatch filter is about 0.6 and 0.8 m in the horizontal and vertical components, respectively. It is about 2 and 1.6 m less than the GNSS chipset solutions, and about 10 and 10 m less than the classical Hatch filter solution, respectively. Moreover, the TT-SD Hatch filter can accurately detect the cycle slips and outliers, and reset the smoothed window in time. It thus avoids the smoothing failure of Hatch filter when a large cycle-slip or an outlier occurs in the observations. Meanwhile, with the aid of the Kalman filter, TT-SD Hatch filter can keep continuously positioning at the sub-meter level. The result of the kinematic experiment demonstrates that the TT-SD Hatch filter solution can converge after a few minutes, and the 2D error is about 0.9 m, which is about 64%, 89%, and 92% smaller than that of the chipset solution, the traditional Hatch filter solution and standard single point solution, respectively. Finally, the TT-SD Hatch filter solution can recover a continuous driving track in this kinematic test.

The availability of raw Android Global Navigation Satellite System (GNSS) data is driving innovation in high-precision positioning using Android smartphones. However, inconsistent pseudorange and phase observations, low dual-frequency data integrity, and unknown receiver-side hardware biases prevent the ambiguity resolution of GNSS precision point positioning (PPP) for smartphones. In this study, we thus provide a comprehensive real-time kinematic precise point positioning (PPP-RTK) strategy. First, carrier phase observations are adjusted to be consistent with the pseudorange observations. Next, rapid single-frequency PPP convergence is achieved by regional atmospheric enhancement. Finally, inter-satellite difference ambiguities are formed to eliminate unknown receiver-side hardware biases and combined with the partial ambiguity resolution strategy to achieve ambiguity-fixed centimeter-level smartphone PPP-RTK positioning. The results show that using the proposed PPP-RTK strategy, the root mean square (RMS) of ambiguity-fixed solution positioning errors is 0.7, 1.3, and 2.5 cm in the east, north, and upper components, respectively, for a representative Huawei P40 smartphone connected to an external survey-type antenna, and 1.2, 1.5, and 5.8 cm for the P40 smartphone using its embedded antenna in an open-sky environment. And their ambiguity fixing rates all reached more than 98%. In 21 sets of experiments, PPP-RTK for smartphones with external and embedded antennas took an average of 1.0 and 63.5 seconds, respectively, to converge to an ambiguity-fixed solution with a horizontal positioning error within 5 cm. This provides a way for rapid and high-precision GNSS positioning in stand-alone mode for smartphones, which may facilitate the development and widespread use of smartphone high-precision GNSS positioning.

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 RMS of the positioning errors in the east, north, and up components in the open-sky environments are 0.18 m, 0.13 m, and 0.38 m, respectively. In complex urban environments, the RMS of the positioning precisions in the east, north, and up components were as decent as 1.42 m, 1.97 m, and 2.63 m, respectively.