How does a GPS satellite tell you where you are?

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1. 1

   Global Positioning System (Wikipedia)

   WikipediaPublished Oct 16, 2026Checked Oct 17, 2026

   “The Global Positioning System (GPS) is a satellite-based hyperbolic navigation system owned by the United States Space Force and operated by Mission Delta 31. It is one of the global navigation satellite systems (GNSS) that provide geolocation and time information to a GPS receiver anywhere on or near the Earth where signal quality permits. It does not require the user to transmit any data, and operates independently of any telephone or Internet reception, though these technologies can enhance the usefulness of the GPS positioning information. It provides critical positioning capabilities to military, civil, and commercial users around the world. Although the United States government created, controls, and maintains GPS, it is freely accessible to anyone with a GPS receiver.”

2. 2

   A New Criterion Construction and Verification for GNSS Satellite Selection Based on Near-Real-Time Accuracy.

   Sensors (Basel, Switzerland) (Zuo et al.)Published Nov 26, 2025Checked Oct 17, 2026

   “Through a sliding window, we estimate the near-real-time accuracy of observations and use it to calculate the Weighted Geometric Dilution of Precision (WGDOP) for satellite selection. In a global International GNSS Service (IGS) station validation experiment, the satellite set selected based on WGDOP using near-real-time accuracy of GFIF and MW observations improved overall positioning accuracy by 11.6% and 12% when compared with the GDOP-based selection, and by 6% and 6.4% when compared with the Signal-to-Noise Ratio (SNR) weighting method. In a low-cost device validation experiment, the satellite selection method based on near-real-time accuracy of GFIF and MW improved positioning accuracy by 22.5% and 19.7% when compared with the GDOP-based method, and by 23.3% and 20.5% when compared with the SNR-based method. A set of dynamic observation experiments further demonstrates that the satellite selection method based on the near-real-time accuracy of GFIF and MW combinations outperforms the other two selection criteria in dynamic scenarios.”

3. 3

   Accuracy of seven GPS-based geolocation techniques versus a surveyor map: a cross-sectional study in a village in the Comoros.

   BMJ open (Dens et al.)Published Aug 26, 2026Checked Oct 17, 2026

   “The remaining four index tests showed little bias (mean measurement error ranging from -1.7 m to 0.4 m across techniques) and low variability (SD of measurement error ranging from 5.7 m to 7.4 m). For the most precise technique, 95% of measurements were estimated to fall between an underestimation of 11.9 m (95% CI 8.9 to 17.5 m) and an overestimation of 10.5 m (95% CI 8.4 to 13.7 m). Even this narrowest range was two to three times wider than the claimed accuracy.ConclusionsGPS-based geolocation techniques may show substantial variability under field conditions and may give rise to misplaced confidence in their accuracy when this is assumed rather than empirically assessed. Careful selection and testing of techniques in context, along with transparent data handling and consideration of uncertainty, are needed to improve the reliability of geospatial data in public health research and practice.”

4. 4

   Improving Smartphone GNSS Positioning Accuracy Using Contextual Information.

   Sensors (Basel, Switzerland) (Park et al.)Published May 25, 2026Checked Oct 17, 2026

   “Consequently, accurate and reliable global satellite navigation system positioning on smartphones has become essential. However, achieving accurate positioning in urban areas remains challenging because of the inherent limitations of smartphones and severe multipath effects. To address this issue, this study proposes two methods to improve positioning accuracy using contextual information. First, an environmental context indicator was used to refine the C/N0-based observation covariance model. Second, normalized C/N0 and code-pseudorange residuals were used to detect non-line-of-sight satellites and adjust the observation covariance. Experiments were conducted in both open and urban areas, and performance was evaluated using circular error probable (CEP) and distance root mean square (DRMS). The experimental results showed that, in open areas, the proposed method achieved submeter to decimeter-level horizontal accuracy and precision. In semi-urban areas, CEP95, CEP50, and DRMS decreased by approximately 8, 2, and 4 m, respectively. In urban canyons, CEP95, CEP50, and DRMS decreased by approximately 15, 2, and 5 m, respectively.”

5. 5

   Characterization of Pseudorange Errors in Hybrid LEO/MEO PNT System.

   Sensors (Basel, Switzerland) (Bianconi et al.)Published Jul 13, 2026Checked Oct 17, 2026

   “Integrating low Earth orbit (LEO) satellites into GNSS (Global Navigation Satellite System) MEO (Medium Earth Orbit) constellations enhances global positioning but faces technical bottlenecks. Through a 1D vehicular scenario simulation using MATLAB-based stochastic modeling of error sources and Least Squares estimation, MEO, LEO and hybrid configurations are evaluated, accounting for ionospheric, atmospheric and multipath errors. Results show that a single LEO satellite fails to improve accuracy due to the absence of onboard atomic clocks and the limitations of using Two-Line Elements (TLEs). However, a threshold of three LEO satellites significantly reduces positioning errors by approximately 35% through effective error averaging. The findings demonstrate that transitioning from TLEs to Precise Orbit Determination (POD) and clock stability are essential for LEO augmentation. These results provide an analytical framework for resilient PNT (Positioning, Navigation and Timing) applications, including autonomous driving and smart cities.”