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Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

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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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Related Experiment Video

Updated: Jun 13, 2025

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3D Positioning of Drones through Images.

Jianxing Yang1, Enhui Zheng1, Jiqi Fan1

  • 1School of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.

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|September 14, 2024
PubMed
Summary
This summary is machine-generated.

This study addresses drone navigation challenges in GPS-denied environments. It introduces a novel method using single images for accurate drone height determination and positioning without satellite support.

Keywords:
deep learningdrone height calculationpositioningunmanned aerial vehicle (UAV)

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Area of Science:

  • Computer Vision
  • Robotics
  • Geospatial Analysis

Background:

  • Drones traditionally rely on satellite navigation (GPS) for positioning and altitude.
  • GPS-denied environments disrupt satellite communication, challenging traditional drone navigation methods.
  • Accurate drone positioning and altitude estimation are critical for safe and effective operation.

Purpose of the Study:

  • To develop a drone positioning and height determination method independent of satellite signals.
  • To evaluate the performance of a proposed multi-scale input network for drone navigation in GPS-denied scenarios.
  • To enable single-image-based height judgment for Unmanned Aerial Vehicles (UAVs).

Main Methods:

  • Creation of a drone dataset captured at altitudes between 80-200 meters.
  • Development and application of a multi-scale input network for positioning.
  • Implementation of UAV image-to-satellite image matching for positioning.
  • Calculation of UAV flight height using image-derived real-space area and optical camera parameters.

Main Results:

  • The proposed positioning index (RDS) achieved 76.3 points.
  • Positioning accuracy within 20 meters was achieved at an 81.7% rate.
  • The method calculated UAV flight height within the 80-200 m range with a relative error rate of 18.1%.
  • Height judgment was successfully performed using single UAV images.

Conclusions:

  • The proposed method offers a viable solution for drone navigation in GPS-denied environments.
  • Image-based height determination and positioning are feasible without external sensor data.
  • This approach enhances drone autonomy and operational capabilities in challenging conditions.