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

Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

201
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...
201
Errors in Global Positioning System01:26

Errors in Global Positioning System

222
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,...
222
Local Attraction01:22

Local Attraction

245
Local attraction refers to disturbances in compass readings caused by magnetic influences from nearby objects such as metal fences, buried pipes, vehicles, buildings, power lines, or natural iron ore deposits. Small items like wristwatches, steel tools, or belt buckles can also interfere with the compass by creating local magnetic fields that distort the Earth's natural magnetic field. These distortions lead to inaccurate readings, posing navigation and land surveying challenges.Local...
245
Field Application of Global Positioning System01:28

Field Application of Global Positioning System

196
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...
196
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

271
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...
271
Introduction to Global Positioning System01:30

Introduction to Global Positioning System

262
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,...
262

You might also read

Related Articles

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

Sort by
Same author

REGγ Links Inflammation to Fibrosis in Post-Necrotizing Enterocolitis Intestinal Strictures by Activating Transforming Growth Factor-β/Smad3 Signaling.

The American journal of pathology·2026
Same author

Vascular Immune Remodeling: A CD4<sup>+</sup> T Cell-Driven Immune Trajectory Associated With Arterial Stiffness.

Aging cell·2026
Same author

Supramolecular Electrostatic-Driven Construction of ZnIn<sub>2</sub>S<sub>4</sub>/NiTCPP Heterojunctions for Efficient Photocatalytic Hydrogen Evolution.

Langmuir : the ACS journal of surfaces and colloids·2026
Same author

AI-guided discovery of the IRF4-PAICS-LDHA axis as a multitarget hub linking tumor metabolism to CD8+ T cell exhaustion in DLBCL.

NPJ precision oncology·2026
Same author

CD27 expression is a clinically accessible biomarker for predicting immunotherapy response in melanoma.

NPJ precision oncology·2026
Same author

Clear cell renal cell carcinoma combined with intravascular large B-cell lymphoma: a case report and review of the literature.

Frontiers in oncology·2026
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Nov 29, 2025

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
04:13

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

Published on: February 8, 2019

7.0K

Time Difference of Arrival Passive Localization Sensor Selection Method Based on Tabu Search.

Qian Li1, Baixiao Chen1, Minglei Yang1,2

  • 1National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China.

Sensors (Basel, Switzerland)
|November 19, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a tabu search method for selecting passive Time Difference of Arrival (TDOA) sensors. The approach optimizes sensor networks for better positioning accuracy while minimizing system consumption and improving timeliness.

Keywords:
constrained total least-squares (CTLS)passive localizationsensor selection optimizationtabu searchtime difference of arrival (TDOA)

More Related Videos

Low-Cost Automated Flight Intercept Trap for the Temporal Sub-Sampling of Flying Insects Attracted to Artificial Light at Night
06:19

Low-Cost Automated Flight Intercept Trap for the Temporal Sub-Sampling of Flying Insects Attracted to Artificial Light at Night

Published on: December 29, 2021

2.9K
Localizing Function-specific Targets for Transcranial Magnetic Stimulation in the Absence of Navigation Equipment
09:30

Localizing Function-specific Targets for Transcranial Magnetic Stimulation in the Absence of Navigation Equipment

Published on: May 23, 2025

1.1K

Related Experiment Videos

Last Updated: Nov 29, 2025

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
04:13

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

Published on: February 8, 2019

7.0K
Low-Cost Automated Flight Intercept Trap for the Temporal Sub-Sampling of Flying Insects Attracted to Artificial Light at Night
06:19

Low-Cost Automated Flight Intercept Trap for the Temporal Sub-Sampling of Flying Insects Attracted to Artificial Light at Night

Published on: December 29, 2021

2.9K
Localizing Function-specific Targets for Transcranial Magnetic Stimulation in the Absence of Navigation Equipment
09:30

Localizing Function-specific Targets for Transcranial Magnetic Stimulation in the Absence of Navigation Equipment

Published on: May 23, 2025

1.1K

Area of Science:

  • Signal Processing
  • Sensor Networks
  • Optimization Algorithms

Background:

  • Passive positioning systems rely on sensor networks for accurate localization.
  • Balancing positioning accuracy with system resource consumption is a critical challenge in sensor network design.
  • Existing methods may not efficiently address the trade-offs between accuracy and resource utilization.

Purpose of the Study:

  • To propose a novel sensor selection method for Time Difference of Arrival (TDOA) passive positioning.
  • To optimize sensor network configuration for enhanced positioning accuracy and reduced system consumption.
  • To develop an efficient algorithm that approximates exhaustive search performance.

Main Methods:

  • Developed a passive TDOA positioning model incorporating sensor position errors.
  • Derived a constrained total least-squares (CTLS) solution and positioning error covariance matrix.
  • Formulated sensor selection as an optimization problem minimizing positioning error covariance trace.
  • Applied tabu search algorithm to efficiently solve the sensor selection problem.

Main Results:

  • The proposed tabu search method achieves sensor selection performance close to exhaustive search.
  • Demonstrated significant reductions in algorithm running time and improvements in timeliness.
  • Successfully balanced positioning accuracy with system consumption in passive TDOA networks.

Conclusions:

  • The tabu search-based sensor selection method is effective for passive TDOA positioning.
  • This approach offers a computationally efficient alternative to exhaustive search for sensor optimization.
  • The method provides a practical solution for improving the performance and efficiency of sensor networks.