Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Field Application of Global Positioning System01:28

Field Application of Global Positioning System

283
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...
283
Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

307
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...
307
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

1.8K
IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
1.8K
Errors in Global Positioning System01:26

Errors in Global Positioning System

304
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,...
304
Elastic Collisions: Case Study01:15

Elastic Collisions: Case Study

20.1K
Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
20.1K
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

357
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...
357

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

PriorNav: Prior Knowledge Enhanced Zero-Shot Goal Navigation via Multi-Step Iterative Reasoning.

Sensors (Basel, Switzerland)·2026
Same author

MS2-CL: Multi-Scale Self-Supervised Learning for Camera to LiDAR Cross-Modal Place Recognition.

Sensors (Basel, Switzerland)·2026
Same author

Asymmetric Double-Sideband Composite Signal and Dual-Carrier Cooperative Tracking-Based High-Precision Communication-Navigation Convergence Positioning Method.

Sensors (Basel, Switzerland)·2025
Same author

A Frontier Review of Semantic SLAM Technologies Applied to the Open World.

Sensors (Basel, Switzerland)·2025
Same author

SGF-SLAM: Semantic Gaussian Filtering SLAM for Urban Road Environments.

Sensors (Basel, Switzerland)·2025
Same author

A Fault-Tolerant Localization Method for 5G/INS Based on Variational Bayesian Strong Tracking Fusion Filtering with Multilevel Fault Detection.

Sensors (Basel, Switzerland)·2025

Related Experiment Video

Updated: Jan 7, 2026

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

8.1K

An Indoor UAV Localization Framework with ESKF Tightly-Coupled Fusion and Multi-Epoch UWB Outlier Rejection.

Jianmin Zhao1, Zhongliang Deng1, Enwen Hu1

  • 1School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.

Sensors (Basel, Switzerland)
|December 31, 2025
PubMed
Summary

This study introduces a new fusion framework for Unmanned Aerial Vehicle (UAV) indoor localization, improving accuracy and robustness by integrating Inertial Measurement Unit (IMU), Ultra-Wideband (UWB), and Visual-Inertial Odometry (VIO) data while rejecting errors.

Keywords:
ESKFIMUNLOSUWBindoor UAV localizationoutlier rejection

More Related Videos

Evaluating Targeting Accuracy in the Focal Plane for an Ultrasound-guided High-intensity Focused Ultrasound Phased-array System
08:08

Evaluating Targeting Accuracy in the Focal Plane for an Ultrasound-guided High-intensity Focused Ultrasound Phased-array System

Published on: March 6, 2019

5.6K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.0K

Related Experiment Videos

Last Updated: Jan 7, 2026

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

8.1K
Evaluating Targeting Accuracy in the Focal Plane for an Ultrasound-guided High-intensity Focused Ultrasound Phased-array System
08:08

Evaluating Targeting Accuracy in the Focal Plane for an Ultrasound-guided High-intensity Focused Ultrasound Phased-array System

Published on: March 6, 2019

5.6K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.0K

Area of Science:

  • Robotics
  • Navigation Systems
  • Sensor Fusion

Background:

  • Unmanned Aerial Vehicles (UAVs) require reliable indoor localization for critical tasks, facing challenges like Global Navigation Satellite System (GNSS) unavailability and sensor limitations.
  • Inertial Measurement Unit (IMU) drift, Ultra-Wideband (UWB) Non-Line-of-Sight (NLOS) biases, and Visual-Inertial Odometry (VIO) feature dependency hinder accurate indoor navigation.
  • Existing localization methods struggle with error accumulation and environmental occlusions, necessitating advanced fusion techniques.

Purpose of the Study:

  • To develop a tightly coupled sensor fusion framework for robust and accurate indoor UAV localization.
  • To address the limitations of individual sensors (IMU, UWB, VIO) in challenging indoor environments.
  • To enhance the stability and reliability of UAV navigation systems.

Main Methods:

  • Proposed a tightly coupled Error-State Kalman Filter (ESKF) framework integrating IMU, UWB ranges, VIO relative poses, and TFmini altitude.
  • Implemented an IMU motion model for prediction and sensor data fusion in the update step.
  • Developed a VIO-constrained multi-epoch outlier rejection method to mitigate UWB NLOS errors and sensor measurement outliers.

Main Results:

  • The proposed fusion framework demonstrated superior localization accuracy and robustness in complex indoor environments compared to existing algorithms.
  • Effectively suppressed Ultra-Wideband (UWB) Non-Line-of-Sight (NLOS) errors and mitigated Inertial Measurement Unit (IMU) and Visual-Inertial Odometry (VIO) drift.
  • Validated on a real-world platform in an underground parking garage, confirming practical applicability.

Conclusions:

  • The tightly coupled ESKF framework significantly enhances indoor UAV localization performance by fusing multiple sensor modalities.
  • The developed outlier rejection method robustly handles challenging UWB measurements, improving overall system reliability.
  • This approach offers a promising solution for accurate and stable UAV navigation in GNSS-denied indoor settings.