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

Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

269
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
269
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

445
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
445
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

526
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
526
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

124
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
124
Non-uniform Circular Motion01:22

Non-uniform Circular Motion

7.5K
In uniform circular motion, the particle executing circular motion has a constant speed, and the circle is at a fixed radius. However, not all circular motion occurs at a constant speed. A particle can travel in a circle and speed up or slow down, showing an acceleration in the direction of motion. In that case, the motion is called non-uniform circular motion, and an additional acceleration is introduced, which is in the direction tangential to the circle. 
For example, such...
7.5K
Relative Motion Analysis - Velocity01:24

Relative Motion Analysis - Velocity

429
A stroke engine has a slider-crank mechanism that converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider.
When an external force is exerted, it sets the crank into a rotational movement. This, in turn, instigates the motion of the connecting rod, leading to what is referred to as a general plane motion. This process involves two key points - point A on the connecting rod...
429

You might also read

Related Articles

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

Sort by
Same author

Vibration-Based Anomaly Detection for Induction Motors Using Machine Learning.

Sensors (Basel, Switzerland)·2025
Same author

3D Off-Grid Localization for Adjacent Cavitation Noise Sources Using Bayesian Inference.

Sensors (Basel, Switzerland)·2023
Same author

A Machine-Learning-Based Robust Classification Method for PV Panel Faults.

Sensors (Basel, Switzerland)·2022
Same author

Improvement in the Tracking Performance of a Maneuvering Target in the Presence of Clutter.

Sensors (Basel, Switzerland)·2022
Same author

Multi-Sonar Distributed Fusion for Target Detection and Tracking in Marine Environment.

Sensors (Basel, Switzerland)·2022
Same author

A Hybrid Newton-Raphson and Particle Swarm Optimization Method for Target Motion Analysis by Batch Processing.

Sensors (Basel, Switzerland)·2021
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: Sep 5, 2025

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
13:02

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

Published on: February 27, 2016

12.4K

Modified Smoothing Algorithm for Tracking Multiple Maneuvering Targets in Clutter.

Sufyan Ali Memon1, Min-Seuk Park1, Imran Memon2

  • 1Department of Defense Systems Engineering, Sejong University, Seoul 05006, Korea.

Sensors (Basel, Switzerland)
|July 9, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces the smoothing Multi-Target Tracking using Joint Integrated Track Splitting (MMT-sJITS) filter, enhancing tracking of maneuvering targets with unknown dynamics. The novel approach reduces computational complexity and improves accuracy in multi-maneuvering-targets (MMT) tracking scenarios.

Keywords:
component existence probabilitiesfalse-track discriminationmulti-maneuvering-targetssmoothingtarget existence probabilities

More Related Videos

Myosin-Specific Adaptations of In vitro Fluorescence Microscopy-Based Motility Assays
08:57

Myosin-Specific Adaptations of In vitro Fluorescence Microscopy-Based Motility Assays

Published on: February 4, 2021

6.1K
Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
07:21

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

Published on: February 12, 2011

14.4K

Related Experiment Videos

Last Updated: Sep 5, 2025

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow
13:02

Three-dimensional Particle Tracking Velocimetry for Turbulence Applications: Case of a Jet Flow

Published on: February 27, 2016

12.4K
Myosin-Specific Adaptations of In vitro Fluorescence Microscopy-Based Motility Assays
08:57

Myosin-Specific Adaptations of In vitro Fluorescence Microscopy-Based Motility Assays

Published on: February 4, 2021

6.1K
Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
07:21

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

Published on: February 12, 2011

14.4K

Area of Science:

  • Signal Processing
  • Data Fusion
  • Target Tracking

Background:

  • Multi-maneuvering-targets (MMT) tracking presents challenges due to unknown target dynamics.
  • Existing fixed interval smoothing based on joint integrated track splitting (FIsJITS) filters are computationally intensive for MMT environments.
  • Accurate tracking of multiple targets with complex motion is crucial in various applications.

Purpose of the Study:

  • To extend the FIsJITS filter for improved MMT tracking.
  • To address the computational complexity and performance limitations of existing MMT tracking algorithms.
  • To develop an efficient method for tracking targets with unknown dynamics.

Main Methods:

  • Introduced the smoothing MMT using JITS (MMT-sJITS) algorithm.
  • MMT-sJITS treats joint measurements from neighbor tracks as modified clutters for optimal estimation.
  • Employs forward and backward track generation and fusion for smoothing estimates.
  • Utilizes Monte Carlo simulations for performance verification.

Main Results:

  • MMT-sJITS significantly reduces computational complexity compared to FIsJITS.
  • The proposed method demonstrates improved tracking performance in MMT scenarios.
  • Enhanced false-track discrimination (FTD) was observed in simulations.
  • Optimal estimation of target measurements concealed by joint measurements was achieved.

Conclusions:

  • MMT-sJITS offers an efficient and effective solution for MMT tracking with unknown dynamics.
  • The algorithm provides a balance between computational load and tracking accuracy.
  • This research contributes to advancing the field of multi-target tracking systems.