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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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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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Basic continuous-time signals include the unit step function, unit impulse function, and unit ramp function, collectively referred to as singularity functions. Singularity functions are characterized by discontinuities or discontinuous derivatives.
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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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Continuous -time Fourier Transform01:11

Continuous -time Fourier Transform

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The Fourier series is instrumental in representing periodic functions, offering a powerful method to decompose such functions into a sum of sinusoids. This technique, however, necessitates modification when applied to nonperiodic functions. Consider a pulse-train waveform consisting of a series of rectangular pulses. When these pulses have a finite period, they can be accurately represented by a Fourier series. Yet, as the period approaches infinity, resulting in a single, isolated pulse, the...
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In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
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GNSS Multipath Detection Using Continuous Time-Series C/N0.

Nobuaki Kubo1, Kaito Kobayashi1, Rei Furukawa1

  • 1Department of Maritime Systems Engineering, Tokyo University of Marine Science and Technology, Tokyo 135-8533, Japan.

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|July 26, 2020
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Summary
This summary is machine-generated.

This study introduces a new Global Navigation Satellite System (GNSS) method using C/N0 signal data to detect and mitigate non-line-of-sight (NLOS) errors, significantly improving positioning accuracy in urban environments.

Keywords:
DGNSSGNSSNLOSRTKmultipathsurvey

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Area of Science:

  • Geomatics Engineering
  • Satellite Navigation Systems
  • Signal Processing

Background:

  • Multipath errors, particularly from non-line-of-sight (NLOS) signals, pose a significant challenge in Global Navigation Satellite System (GNSS) accuracy.
  • Correctly identifying line-of-sight (LOS) satellites is difficult in dense urban areas, even with advanced GNSS receivers.

Purpose of the Study:

  • To develop and validate a novel method for detecting NLOS signals using GNSS C/N0 data.
  • To mitigate multipath errors and enhance the performance of differential GNSS, especially in challenging urban environments.

Main Methods:

  • Utilizing the Carrier-to-Noise density ratio (C/N0) of GNSS signals to identify NLOS signals.
  • Implementing a time-series analysis of C/N0, where a satellite is excluded from positioning if its C/N0 falls below a threshold for a sustained period.
  • Conducting static tests in urban areas with high-rise buildings in Tokyo.

Main Results:

  • The proposed method effectively mitigates multipath errors by reliably removing NLOS signals.
  • The C/N0 time-series analysis proved more robust than simple thresholding in preventing positioning errors caused by fluctuating signals.
  • Substantial improvements in differential GNSS accuracy were observed.

Conclusions:

  • The developed C/N0-based method offers a significant advancement in mitigating multipath errors in GNSS.
  • This approach enhances the reliability and performance of real-time kinematic (RTK) GNSS in complex urban settings.
  • The study demonstrates the effectiveness of analyzing C/N0 time-series for robust NLOS signal detection.