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Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
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GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
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Related Experiment Video

Updated: Jul 11, 2025

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
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SPS: Accurate and Real-Time Semantic Positioning System Based on Low-Cost DEM Maps.

Jun-Xiong Cai, Wensen Feng, Hao-Xiang Chen

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |November 17, 2023
    PubMed
    Summary

    A new Semantic Positioning System (SPS) improves mobile device geo-localization accuracy in urban areas by combining GIS data, GPS, and visual matching. This system offers a robust, real-time solution for applications like Augmented Reality (AR).

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    Area of Science:

    • Computer Vision
    • Geographic Information Systems (GIS)
    • Robotics

    Background:

    • Traditional Global Positioning System (GPS) offers limited accuracy for applications like Augmented Reality (AR).
    • Outdoor urban environments pose challenges for precise mobile device geo-localization due to GPS signal limitations and lack of detailed map data.

    Purpose of the Study:

    • To develop a Semantic Positioning System (SPS) for enhancing mobile device geo-localization accuracy in outdoor urban settings.
    • To enable precise 6 Degree-of-Freedom (DoF) pose estimation by integrating diverse data sources.

    Main Methods:

    • Integration of Geographic Information System (GIS) data, GPS signals, and visual image information.
    • Cross-view semantic matching using Digital Elevation Model (DEM) data and sampled observation pixels with predicted semantic labels.
    • Iterative homography estimation with semantic correspondences and heuristic search for efficient matching.

    Main Results:

    • Achieved 73.24% positioning accuracy on the Bund dataset, outperforming a baseline method by 20%.
    • Improved positioning accuracy by an average of 5% compared to state-of-the-art semantic-based approaches on the Kitti dataset.
    • Demonstrated a robust, real-time, and automatic positioning system with excellent scalability.

    Conclusions:

    • The proposed Semantic Positioning System (SPS) significantly enhances geo-localization accuracy for mobile devices in urban environments.
    • The system effectively overcomes limitations of DEM data by utilizing semantic information for precise pose estimation.
    • SPS provides a scalable and efficient solution for AR and other location-aware applications.