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Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

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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...
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State Space Representation01:27

State Space Representation

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The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
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State Space to Transfer Function01:21

State Space to Transfer Function

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The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
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Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
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Transfer Function to State Space01:23

Transfer Function to State Space

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State-space representation is a powerful tool for simulating physical systems on digital computers, necessitating the conversion of the transfer function into state-space form. Consider an nth-order linear differential equation with constant coefficients, like those encountered in an RLC circuit. The state variables are selected as the output and its n−1 derivatives. Differentiating these variables and substituting them back into the original equation produces the state equations.
In an RLC...
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RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Related Experiment Video

Updated: Jan 13, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
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RTK-GNSS Increment Prediction with a Complementary "RTK-SeqNet" Network: Exploring Hybridization with State-Space

Hassan Ali1,2, Malik Muhammad Waqar1,2, Ruihan Ma1,2

  • 1Department of Electronics and Information Engineering, Jeonbuk National University, Jeonju 54896, Republic of Korea.

Sensors (Basel, Switzerland)
|October 29, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new model to predict Global Navigation Satellite System (GNSS) position changes, improving localization accuracy for autonomous systems during signal outages. The method uses inertial data to maintain precise positioning when GNSS is unavailable.

Keywords:
GNSS outagesGated Recurrent UnitsInertial Measurement UnitRTK-GNSS increment predictionReal-Time Kinematicdeep learning

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Area of Science:

  • Robotics and Autonomous Systems
  • Geomatics Engineering
  • Sensor Fusion

Background:

  • Accurate localization is critical for autonomous systems in dynamic environments like precision agriculture and outdoor robotics.
  • Global Navigation Satellite System (GNSS) technologies, including Real-Time Kinematic (RTK) positioning, offer centimeter-level accuracy but suffer from signal outages and data loss.
  • These GNSS limitations pose significant challenges for reliable navigation in real-world applications.

Purpose of the Study:

  • To propose a novel RTK-like position increment prediction model to mitigate GNSS outages and RTK signal discontinuities.
  • To develop a complementary model that can be integrated into sensor fusion frameworks like the Dual Extended Kalman Filter (Dual EKF).
  • To evaluate the standalone performance of the deep network for predicting position increments during GNSS signal loss.

Main Methods:

  • A deep learning model was developed to predict GNSS position increments.
  • The model utilizes time-synchronized inertial measurement data and velocity inputs.
  • The prediction model was evaluated independently of the Dual EKF sensor fusion framework.

Main Results:

  • The proposed model demonstrated high accuracy in predicting position increments during simulated GNSS outages.
  • Average dynamic time warping (aDTW) across 180-second trajectories was 1.6 meters.
  • Root Mean Square Error (RMSE) averaged 3.4 meters for longer trajectories, with errors below 30 cm for 30-second tests.

Conclusions:

  • The standalone deep network shows promise for complementing GNSS-based localization systems.
  • The developed model can effectively substitute for missing GNSS measurements during outages and RTK signal interruptions.
  • Future work will focus on integrating this prediction model into a Dual EKF sensor fusion framework for enhanced robotic navigation.