Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

IR Frequency Region: Fingerprint Region

IR Frequency Region: Fingerprint Region

IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...

Difference from Background: Limit of Detection

Difference from Background: Limit of Detection

The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...

You might also read

Related Articles

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

Sort by

Same author

Distance and Angle Insensitive Radar-Based Multi-Human Posture Recognition Using Deep Learning.

Sensors (Basel, Switzerland)·2024

Same author

Author Correction: Non-contact diagnosis of obstructive sleep apnea using impulse-radio ultra-wideband radar.

Scientific reports·2024

Same author

Feasibility of Early Assessment for Psychological Distress: HRV-Based Evaluation Using IR-UWB Radar.

Sensors (Basel, Switzerland)·2024

Same author

A Novel Protocol for the Early Detection of COVID-19 at a Skilled Nursing Facility.

Gerontology & geriatric medicine·2024

Same author

Author Correction: Preclinical Evaluation of a Noncontact Simultaneous Monitoring Method for Respiration and Carotid Pulsation Using Impulse-Radio Ultra-Wideband Radar.

Scientific reports·2024

Same author

Author Correction: A public dataset of dogs vital signs recorded with ultra wideband radar and reference sensors.

Scientific data·2024

Search research articles

Related Experiment Video

Updated: Dec 23, 2025

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

A New Thresholding Method for IR-UWB Radar-Based Detection Applications.

Xuanjun Quan¹, Jeong Woo Choi², Sung Ho Cho¹

¹Department of Electronics and Computer Engineering, Hanyang University, 222 Wangsimini-ro, Seongdong-gu, Seoul 04763, Korea.

Sensors (Basel, Switzerland)

|April 25, 2020

Summary

A novel thresholding method for impulse radio ultra-wideband (IR-UWB) radar detection balances false alarms and miss-detections. This approach improves target signal understanding in complex environments by considering clutter and radar parameters.

Keywords:

CFAR IR-UWB radar UWB detection false alarm miss-detection threshold

More Related Videos

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

Wideband Optical Detector of Ultrasound for Medical Imaging Applications

Wideband Optical Detector of Ultrasound for Medical Imaging Applications

Published on: May 11, 2014

Related Experiment Videos

Last Updated: Dec 23, 2025

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

Wideband Optical Detector of Ultrasound for Medical Imaging Applications

Wideband Optical Detector of Ultrasound for Medical Imaging Applications

Published on: May 11, 2014

Area of Science:

Radar Systems Engineering
Signal Processing
Detection Theory

Background:

Thresholding algorithms are critical for radar detection applications, particularly in impulse radio ultra-wideband (IR-UWB) systems.
Existing methods, like Constant False Alarm Rate (CFAR), primarily focus on minimizing false alarms, often neglecting miss-detection rates.

Purpose of the Study:

To introduce a new thresholding method for IR-UWB radar detection that simultaneously addresses both false alarm and miss-detection rates.
To enhance the understanding of target signals within specific environmental conditions, including clutter and radar installation parameters.

Main Methods:

A novel thresholding algorithm is proposed, combining a noise signal-based threshold (focused on false alarms) with a target signal-based threshold (focused on miss-detections) using a designed ratio.
The algorithm objectively sets thresholds by estimating both false alarm and miss-detection rates.
Environmental factors affecting target signals, such as clutter, installation height, and radar angle, are incorporated into the analysis.

Main Results:

The proposed algorithm demonstrates improved performance by considering both false alarm and miss-detection rates.
Thresholds can be objectively set by adjusting the combination ratio and utilizing the algorithm's rate estimation capabilities.
The method provides a better understanding of target signals in diverse environments compared to noise-oriented algorithms.

Conclusions:

The developed thresholding method offers a more comprehensive approach to IR-UWB radar detection by balancing critical error rates.
Experimental validation confirms the algorithm's effectiveness in various scenarios and distances.
This technique enhances target detection reliability by accounting for environmental influences on the target signal.