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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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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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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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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.
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Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
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An Improved UWB/IMU Tightly Coupled Positioning Algorithm Study.

Airu Zou1, Wenwu Hu1, Yahui Luo1

  • 1College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha 410128, China.

Sensors (Basel, Switzerland)
|July 14, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces an improved positioning strategy combining ultra-wide band (UWB) and inertial measurement unit (IMU) to overcome random and non-line-of-sight errors. The novel approach enhances positioning accuracy by 46.15% compared to traditional methods.

Keywords:
extended Kalman filternon-line-of-sighttightly coupled positioningultra-wide band

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Area of Science:

  • Robotics and Navigation
  • Sensor Fusion
  • Geomatics Engineering

Background:

  • Ultra-wide band (UWB) and inertial measurement unit (IMU) systems are crucial for accurate positioning.
  • These systems are susceptible to random errors and non-line-of-sight (NLOS) propagation issues, degrading performance.
  • Existing positioning strategies often struggle to mitigate these error sources effectively.

Purpose of the Study:

  • To develop an improved positioning strategy that integrates UWB and IMU data.
  • To address and mitigate random errors and non-line-of-sight (NLOS) errors inherent in UWB/IMU systems.
  • To enhance the overall positioning accuracy and reliability of combined UWB-IMU systems.

Main Methods:

  • Utilized Kalman Filter (KF) for pre-processing UWB measurements to suppress range mutation.
  • Employed Extended Kalman Filter (EKF) for fusing UWB and IMU measurements, using the difference as measurement information.
  • Incorporated non-line-of-sight (NLOS) measurement information and dynamically adjusted system measurement noise covariance matrix in real-time.
  • Implemented a feedback loop where optimal state estimates dynamically adjust UWB range values for subsequent measurements.

Main Results:

  • The proposed method effectively suppresses the impact of UWB range mutation values on combined positioning.
  • Real-time adjustment of the measurement noise covariance matrix successfully mitigated non-line-of-sight interference.
  • Field experiments demonstrated a significant improvement in positioning accuracy.
  • The developed strategy achieved a 46.15% improvement in positioning accuracy compared to conventional tightly coupled methods.

Conclusions:

  • The improved positioning strategy effectively overcomes the limitations of random and NLOS errors in UWB/IMU systems.
  • The fusion of UWB and IMU data, enhanced by adaptive filtering and NLOS mitigation, leads to superior positioning performance.
  • This approach offers a more robust and accurate solution for navigation and positioning applications.