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Related Concept Videos

Field Application of Global Positioning System01:28

Field Application of Global Positioning System

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The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
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Errors in Global Positioning System01:26

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Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
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Introduction to Global Positioning System01:30

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The Global Positioning System (GPS) revolutionized positioning on Earth, providing precise location data through satellite ranging. The GPS system was developed in 1978 by the U.S. Department of Defense  for military use, and it became available for civilian applications in 1983, transforming fields including navigation, fleet management, and time synchronization for telecommunications systems.GPS consists of satellites in medium Earth orbit, about 20,200 kilometers above the surface,...
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Types of Global Positioning System Surveys01:30

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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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Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

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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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Position and Displacement Vectors01:00

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To describe the motion of an object, one should first be able to describe its position (where it is at any particular time). More precisely, the position needs to be specified relative to a convenient frame of reference. A frame of reference is an arbitrary set of axes from which the position and motion of an object are described. Earth is often used as a frame of reference to describe the position of an object in relation to stationary objects on Earth.
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Updated: Jan 18, 2026

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5G High-Precision Positioning in GNSS-Denied Environments Using a Positional Encoding-Enhanced Deep Residual Network.

Jin-Man Shen1, Hua-Min Chen1, Hui Li1

  • 1School of Information Science and Technology, Beijing University of Technology, Beijing 100124, China.

Sensors (Basel, Switzerland)
|September 13, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new deep learning model, the Positional Encoding Multi-Scale Residual Network (PE-MSRN), for precise 5G positioning in challenging environments. PE-MSRN significantly improves accuracy and speed compared to existing methods.

Keywords:
CSIPE-MSRNdeep residual networkhigh-precision positioningmulti-scale feature extractionpositional encoding

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Area of Science:

  • Wireless communication
  • Deep learning
  • Geospatial positioning

Background:

  • High-precision positioning is crucial for 5G applications but difficult in GNSS-denied areas.
  • Traditional methods struggle with multipath interference and single-source data limitations.

Purpose of the Study:

  • To develop a novel deep learning framework for enhanced 5G positioning accuracy.
  • To leverage 5G Channel State Information (CSI) for improved spatial information mining.

Main Methods:

  • Proposed the Positional Encoding Multi-Scale Residual Network (PE-MSRN) framework.
  • Utilized spatial sampling with multi-granular data and multi-source 5G CSI.
  • Integrated positional encoding (PE) with a multi-scale residual network (MSRN) to process Angle of Arrival (AOA) data.

Main Results:

  • PE-MSRN achieved up to 20 cm positioning accuracy.
  • Demonstrated superior performance over baseline Convolutional Neural Networks (CNNs) and other algorithms.
  • Showcased improved accuracy and faster convergence, especially under real measurement conditions.

Conclusions:

  • PE-MSRN offers a robust solution for high-fidelity 5G positioning systems.
  • The framework effectively mines spatial information from 5G CSI for precise localization.
  • This approach addresses limitations of traditional positioning methods in complex environments.