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

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

354
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
354
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

383
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
383
Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

403
Proportional-Integral (PI) controllers are essential in many control systems to improve stability and performance. They are commonly used in everyday devices like thermostats to enhance system damping and reduce steady-state error. When the zero in the controller's transfer function is optimally placed, the system benefits significantly in terms of stability and accuracy.
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...
403
Range00:59

Range

13.9K
The range is one of the measures of variation. It can be defined as the difference between a dataset's highest and lowest values. For example, in the study of seven 16-ounce soda cans, the filled volume of soda was measured, thus producing the following amount (in ounces) of soda:
15.9; 16.1; 15.2; 14.8; 15.8; 15.9; 16.0; 15.5
Measurements of the amount of soda in a 16-ounce can vary since different subjects record these measurements or since the exact amount - 16 ounces of liquid, was not...
13.9K
Time and frequency -Domain Interpretation of Phase-lead Control01:24

Time and frequency -Domain Interpretation of Phase-lead Control

435
Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
435
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

397
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
397

You might also read

Related Articles

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

Sort by
Same author

GA<sub>3</sub>-loaded hydrophilic and lipophilic diblock polymer acts as a nano-safener to alleviate herbicide-induced rice injury by activating key metabolic pathways.

Plant communications·2026
Same author

An AI-Driven Multimodal Sensing Framework Integrating UAV Imagery and Environmental Sensors for Intelligent Farmland Monitoring.

Sensors (Basel, Switzerland)·2026
Same author

Potentiating mild photothermal therapy via CDK12/13-mediated AKT suppression to orchestrate ferroptosis-apoptosis crosstalk for vaccine-like immunity.

Inflammation research : official journal of the European Histamine Research Society ... [et al.]·2026
Same author

Family engagement in the management of breast cancer-related lymphedema: A qualitative study.

International journal of nursing studies·2026
Same author

m<sup>6</sup>A-modified Mid1 promotes sevoflurane-induced cognitive impairment in neonatal mice by ubiquitin-mediated degradation of Syngap1.

Experimental & molecular medicine·2026
Same author

UCTLFANet: a low-rank fine-tuning model for microalgae image segmentation.

Scientific reports·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: Jan 21, 2026

Real Time Monitoring of Intracellular Bile Acid Dynamics Using a Genetically Encoded FRET-based Bile Acid Sensor
09:21

Real Time Monitoring of Intracellular Bile Acid Dynamics Using a Genetically Encoded FRET-based Bile Acid Sensor

Published on: January 4, 2016

10.4K

Low-Complexity Time-Domain Ranging Algorithm with FMCW Sensors.

Xi Pan1, Chengyong Xiang2, Shouliang Liu3

  • 1School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China. panxi@bit.edu.cn.

Sensors (Basel, Switzerland)
|July 24, 2019
PubMed
Summary
This summary is machine-generated.

A new time-domain ranging algorithm for frequency-modulated continuous wave (FMCW) radar offers high accuracy and low complexity. This method achieves precise distance measurements for short-range radar sensors without needing complex calculations.

Keywords:
beat frequencyfrequency-modulated continuous wavelow-complexitytime-domain ranging

More Related Videos

Polyelectrolyte Complex for Heparin Binding Domain Osteogenic Growth Factor Delivery
12:27

Polyelectrolyte Complex for Heparin Binding Domain Osteogenic Growth Factor Delivery

Published on: August 22, 2016

8.0K
Bacterial Detection & Identification Using Electrochemical Sensors
09:30

Bacterial Detection & Identification Using Electrochemical Sensors

Published on: April 23, 2013

28.9K

Related Experiment Videos

Last Updated: Jan 21, 2026

Real Time Monitoring of Intracellular Bile Acid Dynamics Using a Genetically Encoded FRET-based Bile Acid Sensor
09:21

Real Time Monitoring of Intracellular Bile Acid Dynamics Using a Genetically Encoded FRET-based Bile Acid Sensor

Published on: January 4, 2016

10.4K
Polyelectrolyte Complex for Heparin Binding Domain Osteogenic Growth Factor Delivery
12:27

Polyelectrolyte Complex for Heparin Binding Domain Osteogenic Growth Factor Delivery

Published on: August 22, 2016

8.0K
Bacterial Detection & Identification Using Electrochemical Sensors
09:30

Bacterial Detection & Identification Using Electrochemical Sensors

Published on: April 23, 2013

28.9K

Area of Science:

  • * Electrical Engineering
  • * Signal Processing
  • * Radar Systems

Background:

  • * Frequency-modulated continuous wave (FMCW) radar is widely used for short-range sensing applications.
  • * Traditional ranging algorithms, such as Fast Fourier Transform (FFT), often require significant computational resources and are limited by frequency bandwidth for accuracy.
  • * There is a need for high-accuracy, low-complexity ranging algorithms suitable for real-time implementation in cost-effective systems.

Purpose of the Study:

  • * To propose and validate a novel time-domain ranging algorithm for FMCW radar sensors.
  • * To enhance ranging accuracy and reduce computational complexity compared to existing methods.
  • * To analyze the algorithm's performance under various operational conditions.

Main Methods:

  • * Development of a time-domain algorithm that estimates distance by calculating the ratio of beat frequency to its derivative.
  • * Elimination of the frequency bandwidth restriction on ranging accuracy.
  • * Fabrication of an FMCW sensor prototype and construction of a measurement system for experimental validation.

Main Results:

  • * The proposed time-domain algorithm achieved a range error within 0.8 meters in testing.
  • * Error analysis demonstrated robustness across different distances, integral lengths, relative velocities, and signal-to-noise ratios (SNRs).
  • * The algorithm avoids complex multiplications, unlike the conventional FFT method.

Conclusions:

  • * The developed time-domain algorithm provides a high-accuracy, low-complexity solution for FMCW radar ranging.
  • * Its computational efficiency makes it suitable for real-time, low-cost system integration.
  • * The algorithm overcomes limitations of bandwidth-dependent accuracy seen in traditional FFT-based schemes.