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

Errors in Global Positioning System01:26

Errors in Global Positioning System

45
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,...
45

You might also read

Related Articles

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

Sort by
Same author

The relationship between diabetic retinopathy and intestinal microbiota: a systematic review and meta analysis.

International ophthalmology·2026
Same author

Correction: circNFIB1 inhibits lymphangiogenesis and lymphatic metastasis via the miR-486-5p/PIK3R1/VEGF-C axis in pancreatic cancer.

Molecular cancer·2026
Same author

Genome-wide identification of the CsLBD gene family in tea plant and functional characterization of CsAS2 in tea leaf development.

Plant physiology and biochemistry : PPB·2026
Same author

AI-ECG for Echocardiography Triage in Structural Heart Disease: Evidence, Implementation, and Future Directions.

International journal of general medicine·2026
Same author

CsSPX-PHR/PHL-PHT1 and CsmiR399a-PHO2-PHT1/PHO1 Modules Orchestrate Pi Use Efficiency and Aluminium Tolerance in Tea Plants.

Plant, cell & environment·2026
Same author

Synergistic enhancement of industrial adaptability in Lactiplantibacillus plantarum BF_15 through glutathione-mediated redox and DNA repair pathways.

World journal of microbiology & biotechnology·2026

Related Experiment Video

Updated: Jul 2, 2025

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

578

Improved SSA-Based GRU Neural Network for BDS-3 Satellite Clock Bias Forecasting.

Hongjie Liu1, Feng Liu1, Yao Kong2

  • 1College of Computer Science, Xi'an Polytechnic University, Xi'an 710600, China.

Sensors (Basel, Switzerland)
|February 24, 2024
PubMed
Summary

This study introduces the ITSSA-GRU model for forecasting satellite clock bias in the BeiDou Navigation Satellite System (BDS-3). The novel approach enhances prediction accuracy for high-precision global navigation satellite system (GNSS) positioning.

Keywords:
GRU neural networkSSAsatellite clock bias

More Related Videos

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

783
AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells
06:03

AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells

Published on: June 23, 2023

472

Related Experiment Videos

Last Updated: Jul 2, 2025

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

578
Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

783
AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells
06:03

AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells

Published on: June 23, 2023

472

Area of Science:

  • Satellite navigation systems
  • Geodesy and geomatics engineering
  • Artificial intelligence in navigation

Background:

  • Satellite clock errors significantly impact Global Navigation Satellite System (GNSS) positioning accuracy.
  • Accurate forecasting of satellite clock bias is crucial for high-precision positioning applications.
  • Existing models like Gated Recurrent Unit (GRU) face challenges with hyperparameter sensitivity and local optima.

Purpose of the Study:

  • To develop an advanced satellite clock bias forecasting model for the BeiDou Navigation Satellite System (BDS-3).
  • To improve the prediction accuracy and stability of existing neural network models.
  • To enhance the optimization capabilities for satellite clock bias forecasting.

Main Methods:

  • Implementation of a novel Improved Sparrow Search Algorithm (ITSSA) combined with a Gated Recurrent Unit (GRU) neural network (ITSSA-GRU).
  • Enhancement of the Sparrow Search Algorithm (SSA) with iterative chaotic mapping for population initialization and t-step optimization for iterative updates.
  • Comparative analysis of ITSSA-GRU against GRU, Long Short-Term Memory (LSTM), and GM(1,1) models using BDS-3 satellite clock bias data from MEO, IGSO, and GEO orbits.

Main Results:

  • The ITSSA-GRU model demonstrated superior generalization ability and forecasting performance across all tested satellite orbit types (MEO, IGSO, GEO).
  • The proposed model significantly outperformed SSA-GRU, GRU, LSTM, and GM(1,1) in predicting satellite clock bias.
  • The enhanced optimization strategy within ITSSA effectively addressed GRU's limitations.

Conclusions:

  • The ITSSA-GRU model offers a robust and accurate solution for satellite clock bias forecasting in the BDS-3 system.
  • This new method provides a valuable tool for enhancing the precision of GNSS positioning.
  • The findings highlight the potential of hybrid AI-optimization approaches for improving satellite navigation accuracy.