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相关概念视频

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

Types of Global Positioning System Surveys

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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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Random Error01:04

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Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
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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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Classification of Signals01:30

Classification of Signals

381
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
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Introduction to Global Positioning System01:30

Introduction to Global Positioning System

46
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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Updated: May 31, 2025

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对GNSS时间序列数据的错误特征分析和过算法.

Hongli Zhang1, Yijin Chen1, Kemeng Li1

  • 1College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China.

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概括
此摘要是机器生成的。

这项研究增强了来自移动模块的低精度全球导航卫星系统 (GNSS) 数据. 分析时间错误模式和应用过方法可显著提高区域监测的测量准确性和可靠性.

关键词:
错误补偿 错误补偿 错误补偿 错误补偿过算法的过算法时间序列数据数据时间序列数据

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科学领域:

  • 地理学工程 工程地质学
  • 环境监测 环境监测
  • 数据科学数据科学数据科学

背景情况:

  • 固定和移动的全球导航卫星系统 (GNSS) 模块用于像露天矿山这样的环境.
  • 移动GNSS模块提供了诸如低功耗和成本等优势,但精度较低,限制其用于近似定位.
  • 处理大量低精度GNSS数据对于提取有价值的信息至关重要.

研究的目的:

  • 开发一种方法来提高低精度移动GNSS数据的准确性和可靠性.
  • 分析特定时空区域内GNSS测量中的时间误差变化模式.
  • 为测量误差变化制定一个一般方程,并应用过技术.

主要方法:

  • 对影响特定时空区域测量精度的因素进行全面分析.
  • 对GNSS数据进行时间分析,以确定测量误差变化模式.
  • 应用过方法来提高数据质量.

主要成果:

  • 在相同的时间段和区域内,具有相似精度的设备的测量误差模式是一致的.
  • 过方法提高了测量精度84.4%至95.9%.
  • 可靠性增加了58.2%至73.2%在95%的置信度水平.

结论:

  • 来自类似精度设备的时间GNSS数据在区域时空条件下表现出一致的错误分布模式.
  • 拟议的过方法显著提高了低精度GNSS测量的准确性和可靠性.
  • 这种方法可以更有效地利用移动GNSS数据用于采矿中的车辆管理等应用.