• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.455-465
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• 2024

In shallow water, the array invariant, known as the effective range estimation method, is developed based on the broadband dispersion characteristics in an ideal waveguide, which can be summarized by the waveguide invariant. It is robust enough to estimate both the array tilt and range simultaneously, even in situations where array tilt exists. Recently, it has been extended to fully consider the angle dependence of the waveguide invariant. However, applying the array invariant in range-dependent environments instead of range-independent environments can lead to range estimation errors due to bathymetry mismatch. In this paper, we interpret such range estimation errors by introducing the concept of effective range. Through numerical simulations and experimental data in a weakly range-dependent environment, we demonstrate the relationship between range estimation errors and effective range.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.466-475
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• 2024

Matched-Field Processing (MFP) is a model-based approach that requires accurate knowledge of the ocean environment and array geometry (e.g., array tilt) to localize underwater acoustic sources. Consequently, it is inherently sensitive to model mismatches. In contrast, the waveguide invariant-based approach (also known as array invariant) offers a simple and robust means for source-range estimation in shallow waters. This approach solely exploits the beam angles and travel times of multiple arrivals separated in the beam-time domain, requiring no modeling of the acoustic fields, unlike MFP. This paper extends the waveguide invariant-based approach to shallow water environments featuring a shallow pit, where the waveguide invariant is not defined due to the complex bathymetry. An in-depth performance analysis is conducted using experimental data and numerical simulations.

• The Journal of the Acoustical Society of Korea
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• v.38 no.2
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• pp.231-239
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• 2019

In sonar systems, the passive ranging of a target is an active research area. This paper analyzed the performance of passive ranging based on an array invariant method for different environmental and sonar parameters. The array invariant developed for source range estimation in shallow water. The advantages of this method are that detailed environmental information is not required, and the real-time ranging is possible since the computational burden is very small. Simulation was performed to verify the algorithm. And this method is applied to sea-going experimental data in 2013 near Jinhae port. This study shows the performance of ranging for source orientation, transmission signal length, and length of a receiver through numerical simulation experiments. Also, the results using nested array and uniform line arrays are compared.

• The Journal of the Acoustical Society of Korea
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• v.25 no.6
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• pp.305-311
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• 2006

In this paper the performance of a array invariant method is evaluated for source-range estimation in horizontally stratified shallow water ocean waveguide. The method has advantage of little computationally effort over existing source-localization methods. such as matched field processing or the waveguide invariant and array gain is fully exploited. And. no knowledge of the environment is required except that the received field should not be dominated by purely interference This simple and instantaneous method is applied to simulated acoustic propagation filed for testing range estimation performance. The result of range estimation according to the SNR for the underwater impulsive source with broadband spectrum is demonstrated. The spatial smoothing method is applied to suppress the effect of mutipath propagation by high frequency signal. The result of performance test for range estimation shows that the error rate is within 20% at the SNR above 10dB.

• Journal of the Korean Geophysical Society
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• v.9 no.2
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• pp.99-103
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• 2006

3D object recognition independent of translation and rotation using an ultrasonic sensor array, invariant moment vectors and SOFM(Self Organizing Feature Map) neural networks is presented. Using invariant moment vectors of the acquired 16×8 pixel data of square, rectangular, cylindric and regular triangular blocks, 3D objects could be classified by SOFM neural networks. Invariant moment vectors are constant independent of translation and rotation. The recognition rates for the training and testing data were 95.91% and 92.13%, respectively.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1237-1239
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• 1996

3-D object recognition and restoration independent of the translation and rotation using an ultrasonic sensor array, neural networks and invariant moment are presented. Using invariant moment vectors on the acquired $16{\times}8$ pixel data, 3-D objects can be classified by SOFM(Self Organizing Feature Map) neural networks. Invariant moment vectors kept constant independent of the translation and rotation. The experiment result shows the suggested method can be applied to the environment recognition.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.23-29
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• 2017

A concept of a VSA (Virtual Source Array) is the method for an acoustic spatio-temporal focus at a selected location in the outbound direction with respect to the VSA without the need of a probe source as combines a TRP (Time-Reversal Processing) and time-delay and beam-steering. However, in TRP using the VSA concept, it is limited to the critical angle and the short distances relevant to the VSA. In this paper, the waveguide invariant theory is applied to the VSA concept to refocus the received field at ranges greater other than the critical angle and the short ranges by shifting the focused field. The suggested method is verified via numerical simulation, and the results show that the robust acoustic focusing is achieved on the selected location regardless of the limitation on the conventional VSA concept.

• Current Optics and Photonics
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• v.3 no.4
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• pp.285-291
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• 2019

We have studied the behavior of light in the intermediate regime between a single nanoslit and an infinite nanoslit array. We first calculated the optical characteristics of a small number of nanoslits using finite element numerical analysis. The phase variance of the proposed nanoslit model shows a gradual phase shift between a single nanoslit and ideal nanoslit array, which stabilizes before the total array length becomes ${\sim}0.5{\lambda}$. Next, we designed a transmission-enhanced Fresnel zone plate by applying the phase characteristics from the small-number nanoslit model. The virtual-point-source method suggests that the proposed Fresnel zone plate with phase-invariant nanoslits achieves 2.34x higher transmission efficiency than a conventional Fresnel zone plate. Our report describes the intermediate behaviors of a nanoslit array, which could also benefit subwavelength metallic structure research of metasurfaces.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.10 no.4
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• pp.78-84
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• 1996

In this study, 3-D object recognition and restoration independent of the object translation for automotive kind recognition in parking administration system using an ultrasonic sensor array, neural networks and invariant moments are presented. Using invariant moment vectors of the acquired data 16$\times$8 pixels, 3-D objects could be classified by SCL (Simple Competitive Learning) neural networks. Modified SCL neural networks using the 16$\times$8 low resolution image was used for object restoration of 32$\times$32 high resolution image. Invariant moment vectors kept constant independent of the object translation. The recognition rates for the training and the testing data were 98[%] and 95[%], respectively. The experimental results have shown that ultrasonic sensor array with the neural networks could be applied for the detection of the automobiles and classification of the automotive kind.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.179-187
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• 2010

Miniature spectrometers can be applied for various purposes in wide areas. This paper shows how a wellmade spectrometer on-a-chip of a low performance and low-cost filter-array can be used for recognizing types of red wine. Light spectra are processed through a filter-array of a spectrometer after they have passed through the wine in the cuvettes. Without recovering the original target spectrum, pattern recognition methods are introduced to detect the types of wine. A wavelength cross-correlation turns out to be a good distance metric among spectra because it captures their simultaneous movements and it is affine invariant. Consequently, a well-designed spectrometer is reliability in terms of its repeatability.