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Errors in Global Positioning System01:26

Errors in Global Positioning System

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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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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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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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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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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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An Elastic Filtering Algorithm with Visual Perception for Vehicle GNSS Navigation and Positioning.

Wenzhuo Ma1, Zhe Yue1, Zengzeng Lian1

  • 1School of Surveying and Mapping, Henan Polytechnic University, Jiaozuo 454003, China.

Sensors (Basel, Switzerland)
|January 8, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an elastic filtering algorithm using visual perception to improve Global Navigation Satellite System (GNSS) positioning accuracy for vehicles in cities. The new method significantly enhances real-time navigation precision, especially in complex urban environments.

Keywords:
elastic filteringinter-frame differential optical flow methodvehicle GNSS navigation and positioningvisual perception

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Area of Science:

  • * Robotics and Autonomous Systems
  • * Computer Vision
  • * Geomatics Engineering

Background:

  • * Precise real-time vehicle positioning in urban environments is critical but challenging for current Global Navigation Satellite System (GNSS) algorithms.
  • * Existing Kalman filter-based GNSS methods lack the required accuracy due to urban complexities.
  • * The synergy between navigation and visual perception offers potential for enhanced positioning.

Purpose of the Study:

  • * To develop an elastic filtering algorithm integrated with visual perception for improved vehicle GNSS navigation and positioning.
  • * To enhance the precision of GNSS navigation by adapting filtering models to different vehicle states.
  • * To address the challenge of frequent stationary periods in urban driving for more accurate localization.

Main Methods:

  • * Utilized a visual perception system to capture real-time environmental data and assess driving status via interframe differential optical flow and vehicle state switching.
  • * Designed a state-adaptive elastic filtering model to improve Kalman filter-based GNSS accuracy.
  • * Incorporated a zero-speed constraint to refine location data during stationary periods, matching it with the appropriate elastic filtering model.

Main Results:

  • * The proposed elastic filtering algorithm demonstrated significant improvements in vehicle GNSS navigation and positioning accuracy in urban settings through simulations and real-world experiments.
  • * Outperformed conventional algorithms and the interactive multi-model (IMM) algorithm.
  • * Achieved 3D positioning accuracy enhancements of 21.8%, 20.9%, and 31.3% compared to the advanced IMM model.

Conclusions:

  • * The elastic filtering algorithm with visual perception provides a robust solution for accurate vehicle GNSS positioning in challenging urban environments.
  • * The algorithm's adaptability to various vehicle states and its zero-speed constraint effectively enhance localization precision.
  • * This approach represents a significant advancement over existing methods for real-time urban navigation systems.