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Related Concept Videos

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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Common Leveling Mistakes and Errors01:17

Common Leveling Mistakes and Errors

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A survey team is tasked with determining the elevation difference between points Point A and Point B, separated by uneven terrain. They use a leveling instrument and a leveling rod.Common MistakesMisreading the Rod: During a backsight reading at Point A, the instrumentman observes the rod partially obscured by tall grass. Instead of reading 1.135 m, they mistakenly record 1.735 m due to the misalignment of the crosshair with the wrong graduation. This error adds 0.600 m to all subsequent...
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Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

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

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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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Errors in Taping01:18

Errors in Taping

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Errors in taping arise from multiple factors that can significantly impact measurement accuracy in surveying. Misalignment of the tape, often due to human error, is one primary source. A skilled rear tapeman, using a telescope, can help correct alignment by guiding the head tapeman; however, human limitations still lead to small inaccuracies. These errors may include misplacement of pins or inaccurate tape readings due to common visual confusions, such as mistaking a six for a nine. Such...
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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
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Distance Corrections01:15

Distance Corrections

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To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
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Detecting Positioning Errors and Estimating Correct Positions by Moving Window.

Ha Yoon Song1, Jun Seok Lee1

  • 1Department of Computer Engineering, Hongik University, Seoul, Korea.

Plos One
|December 2, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a new algorithm to detect and correct errors in smart device positioning data. The method uses a moving window approach to ensure accurate location tracking for applications and mobility research.

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Area of Science:

  • Computer Science
  • Geomatics Engineering
  • Data Science

Background:

  • Smart mobile devices offer advanced positioning capabilities used in numerous applications.
  • Environmental factors frequently introduce errors into positioning data, compromising data integrity.
  • Accurate positioning data is crucial for applications ranging from navigation to human mobility research.

Purpose of the Study:

  • To develop and validate an algorithm for detecting erroneous positioning data from smart mobile devices.
  • To estimate correct positioning data and mitigate the impact of errors on subsequent analyses.
  • To enhance the reliability of positioning data for research in human mobility and related fields.

Main Methods:

  • An algorithm based on a moving window approach to analyze speed values derived from consecutive positioning data.
  • Utilizing moving average and standard deviation within the window to define a significant interval for error detection.
  • Incorporating physical parameters and window settings to refine the detection and estimation process.

Main Results:

  • The algorithm successfully detects erroneous positioning data by analyzing speed values against a dynamic interval.
  • The proposed method accurately estimates correct positions after identifying and filtering erroneous data points.
  • The algorithm effectively removes error effects on moving window statistics, maintaining high accuracy.

Conclusions:

  • The developed algorithm provides a robust solution for identifying and correcting errors in smart device positioning data.
  • This approach enhances the accuracy and reliability of positioning data, benefiting various applications.
  • The research contributes a valuable tool for researchers working with positioning data and human mobility studies.