Related Experiment Video
Updated: Jun 21, 2026
05:52
Analyzing the Movement of the Nauplius 'Artemia salina' by Optical Tracking of Plasmonic Nanoparticles
Published on: July 15, 2014
10.5K
Adaptive Steered Frequency-Wavenumber Analysis for High-Frequency Source Localization in Shallow Water
Y H Choi1, Gihoon Byun2, Donghyeon Kim3
1Department of Ocean Engineering, Korea Maritime and Ocean University, Busan 49112, Republic of Korea.
Sensors (Basel, Switzerland)
|April 12, 2025
Summary
This study enhances source localization in shallow waters using the steered frequency-wavenumber (SFK) analysis method. Adaptive techniques improve performance for high-frequency signals, accurately pinpointing sound sources even in challenging environments.
Area of Science:
- Underwater acoustics
- Array signal processing
- Bioacoustics
Background:
- Conventional array signal processing struggles with shallow-water source localization above 1 kHz due to environmental mismatch.
- The steered frequency-wavenumber (SFK) analysis method offers a solution by integrating beam-steering into frequency-wavenumber analysis.
- This enables target localization in sparse conditions with high-frequency signals.
Purpose of the Study:
- To extend the SFK method by incorporating adaptive signal processing techniques.
- To evaluate the performance of minimum-variance distortionless response (MVDR) and white noise gain constraint (WNG) methods within the SFK framework.
- To compare the performance of these adaptive SFK methods against the Bartlett SFK approach.
Main Methods:
- Application of adaptive signal processing techniques, specifically MVDR and WNG, to the SFK method.
- Localization of snapping shrimp sounds (5–24 kHz, 0.2 ms duration) using a sparse vertical array (16 sensors, 60-m aperture) in 100-m shallow water.
- Comparison of localization accuracy between adaptive SFK methods and the Bartlett SFK approach.
Main Results:
- The adaptive SFK methods demonstrated improved source localization performance compared to the Bartlett SFK approach.
- Accurate localization of a snapping shrimp sound source was achieved at a range of 38 m and a depth of 99.8 m.
- The study validates the effectiveness of adaptive SFK for high-frequency source localization in challenging shallow-water environments.
Conclusions:
- Adaptive signal processing techniques significantly enhance the steered frequency-wavenumber (SFK) method for shallow-water source localization.
- The extended SFK method, particularly with MVDR and WNG, provides robust high-frequency target localization even with sparse sensor arrays.
- This research offers a valuable advancement for underwater acoustic monitoring and source identification in complex environments.
Related Concept Videos
01:21Frequency-dependent Selection
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.Positive Frequency-Dependent SelectionIn positive...
01:08Determination 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...
01:20Discrete-Time Fourier Series
The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
For a discrete-time periodic signal x[n]...
For a discrete-time periodic signal x[n]...
01:18Aliasing
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 signal...
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
01:24Frequency-Domain Interpretation of PD Control
Proportional-Derivative (PD) controllers are widely used in fan control systems to improve stability and performance. A fan control system can be effectively represented using a Bode plot to illustrate the impact of a PD controller through its transfer function. The Bode plot visually conveys how PD control modifies the fan's response across various frequencies, providing a frequency domain interpretation of the controller's behavior.
The proportional control gain, combined with the system's...
The proportional control gain, combined with the system's...
01:24Time and frequency -Domain Interpretation of Phase-lead Control
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...
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...