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

Determination of Expected Frequency

Determination of Expected Frequency

Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...

Linear Approximation in Frequency Domain

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....

Field Application of Global Positioning System

Field Application of Global Positioning System

The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...

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...

Aliasing

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...

IR Frequency Region: X–H Stretching

IR Frequency Region: X–H Stretching

In IR spectroscopy, signals produced by the X−H bonds (such as C−H, O−H, or N−H) can be observed in the frequency range of 2700–4000 cm–1. The C−H stretching vibration forms sharp bands in the region 2850–3000 cm–1. The presence of the O−H stretching vibration leads to the forming of an absorption band in the frequency range 3650–3200 cm−1. At the same time, N−H stretching can be confirmed by absorption bands in...

You might also read

Related Articles

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

Sort by

Same author

Multi-Targeting Carnosic Acid Kills Drug-Resistant Helicobacter pylori With Narrow-Spectrum Activity.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Same author

Association between single-point insulin sensitivity estimator and three-vessel coronary disease: a cross-sectional study.

Frontiers in endocrinology·2026

Same author

Nitrogen-Atom Insertion of Indolyl Phosphonium Salts through C-P and C-C Bond Functionalization.

Organic letters·2026

Same author

Coherent multi-beam ray-based blind deconvolution with curvature compensation for channel impulse response estimation.

JASA express letters·2026

Same author

Distinctive acoustic multipath propagation over a low velocity layer of sediments in deep ocean.

The Journal of the Acoustical Society of America·2026

Same author

Association between the composite nutritional index TCBI and ISR.

Frontiers in nutrition·2026

Search research articles

Related Experiment Video

Updated: Mar 27, 2026

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans

Published on: May 19, 2016

Frequency-unknown matched field processing for frequency estimation and localization.

Xian Yan^1,2,3,4, Shengchun Piao^1,2,3,4, Qian Tong^1,2,3,4

¹National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China.

The Journal of the Acoustical Society of America

|March 25, 2026

Summary

This summary is machine-generated.

Frequency-unknown matched field processing (FU-MFP) estimates source frequency and location using signal inversion. This advanced method improves upon conventional MFP, especially in low signal-to-noise ratio environments.

More Related Videos

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples

Published on: June 9, 2016

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

Related Experiment Videos

Last Updated: Mar 27, 2026

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans

Published on: May 19, 2016

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples

Published on: June 9, 2016

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

Area of Science:

Acoustics
Signal Processing
Oceanography

Background:

Matched field processing (MFP) traditionally requires known source frequencies.
Unknown source frequencies necessitate estimation from received signals.
Conventional MFP struggles with unknown frequency and low signal-to-noise ratio (SNR) conditions.

Purpose of the Study:

To develop and evaluate frequency-unknown matched field processing (FU-MFP).
To enhance source localization and frequency estimation in challenging acoustic environments.
To improve performance in low SNR conditions.

Main Methods:

Incoherent FU-MFP incorporates inversion of transmission frequency and radial velocity for motion compensation.
Coherent FU-MFP combines passive synthetic aperture processing with motion compensation.
Extended Fourier transform windows are utilized through radial velocity inversion.

Main Results:

FU-MFP successfully estimates source frequency and location in low SNR.
Coherent FU-MFP achieves localization using weak line spectrum signals.
Simulations and experiments demonstrate FU-MFP significantly outperforms conventional MFP.

Conclusions:

FU-MFP provides robust source localization and frequency estimation.
The proposed coherent FU-MFP method is effective for weak signals in low SNR.
This technique offers a significant advancement over traditional MFP for unknown frequency scenarios.