Passive acoustic detection and classification of divers in harbor environments

Lennartsson, R.K.; Dalberg, E.; Persson, Leif; Petrovic, S.

doi:10.23919/oceans.2009.5422407

Cited by 12 publications

(4 citation statements)

References 5 publications

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“…e distance from the node to the acoustic receiving center is r. e electric charge Q of the node is measured at the positive pole of the ceramic disk. erefore, the current is [27] I zQ zt jωQ j2πfQ, (13) where t stands for time, j is an imaginary sign, and f is the vibration frequency of acoustic waves. e transmitting current response level SIL is…”

Section: Receiving Sensitivitymentioning

confidence: 99%

“…Especially when deployed around a large military ship, passive sonar is difficult for opposing forces to detect. Moreover, it can identify a target more easily based on the various acoustical characteristics of different targets [2,13]. For this reason, a low frequency, small, very sensitive, and low-cost transducer should be designed to improve the detection of underwater frogmen.…”

Section: Introductionmentioning

confidence: 99%

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Structural Design and Test of a Piezoelectric Flextensional Transducer for Passive Detection of Frogmen

Sun

Chen

et al. 2022

Mathematical Problems in Engineering

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A piezoelectric flextensional transducer was designed using the finite element method (FEM) for the passive detection of underwater frogmen. By studying the main performance parameters of sonar transducers for the detection of frogmen around the world, this paper presents the advantages of active and passive sonar in this task and proposes a passive method for the detection of frogmen. Subsequently, a Cymbal transducer was selected considering the needs of the research. After introducing the principles and methods of the FEM analysis, the acoustic and electromechanical characteristics of the Cymbal transducer were verified under the influence of structural dimensions, e.g., resonance frequency, conductance, and susceptance. The electromechanical performance of the Cymbal transducer was simulated with a FEM to study how it is affected by static water pressure and processing errors and to demonstrate the feasible application of the Cymbal transducer in practical applications. In the end, a Cymbal prototype was tested to verify that the designed Cymbal transducer performs in compliance with the requirements and can be used for the passive detection of underwater frogmen with open-circuit breathing.

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Section: Receiving Sensitivitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Structural Design and Test of a Piezoelectric Flextensional Transducer for Passive Detection of Frogmen

Sun

Chen

et al. 2022

Mathematical Problems in Engineering

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show abstract

“…Since then, there have been many variations of the DEMON algorithm proposed to solve different specific problems, such as the tracking of multiple sources in a decoupled way [ 8 ], and 3/2D spectral analysis to extract propeller features from acoustic vector sensor data [ 9 ]. The basic DEMON algorithm has been tested in practice [ 10 ] and has also been used to detect the breathing pattern of divers from recorded data [ 11 ]. These above analyses are based on spectral estimation to detect and classify targets.…”

Section: Introductionmentioning

confidence: 99%

Classification of Surface Vehicle Propeller Cavitation Noise Using Spectrogram Processing in Combination with Convolution Neural Network

Bach¹,

Vu²,

Nguyen

2021

Sensors

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This paper proposes a method to enhance the quality of detecting and classifying surface vehicle propeller cavitation noise (VPCN) in shallow water by using the improved Detection Envelope Modulation On Noise (DEMON) algorithm in combination with the modified Convolution Neural Network (CNN). To improve the quality of the VPCN spectrogram signal, we apply the DEMON algorithm while analyzing the amplitude variation (AV) to detect the fundamental frequencies of the VPCN signal. To enhance the performance of the traditional CNN, we adapt the size of the sliding window in accordance with the properties of the VPCN spectrogram data, and also reconstruct the CNN layer structure. As for the results, the fundamental frequencies contented in the VPCN spectrogram data can be detected. The analytical results based on the measured data show that the accuracy of the VPCN classification obtained by the proposed method is above 90%, which is higher than those obtained by traditional methods.

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“…Extensive work in the same estuarine environment was conducted by Stolkin et al (2006), Stolkin and Florescu (2007), Bunin et al (2007), Borowski et al (2008), and , giving detection distance of more than 100 m for single hydrophone using a noncoherent envelope processor. Lennartsson et al (2009), Johansson et al (2010), and Lennartsson et al (2010) conducted several sea trials with single hydrophones, a six hydrophone array, and electric underwater sensors. Detection distances for the port of Gothenburg (Sweden) were on the order of 30 m for a single hydrophone.…”

Section: Introductionmentioning

confidence: 99%

Partial dereverberation used to characterize open circuit scuba diver signatures

Gemba

Nosal

Reed

2014

The Journal of the Acoustical Society of America

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The use of passive acoustics to detect self-contained underwater breathing apparatus (SCUBA) divers is useful for nearshore and port security applications. While the performance of a detector can be optimized by understanding the signal's spectral characteristics, anechoic recording environments are generally not available or are cost prohibitive. A practical solution is to obtain the source spectra by equalizing the recording with the inverse of the channel's impulse response. This paper presents a dereverberation method for signal characterization that is subsequently applied to four recorded SCUBA configurations. The inverse impulse response is computed in the least-square sense, and partial dereverberation of SCUBA is performed over the 6-18 kHz band. Results indicate that early reflections and late reverberation added as much as 6.8 dB of energy. Mean unadjusted sound pressure levels computed over the 0.3-80 kHz band were 130 ± 5.9 dB re 1 μPa at 1 m. Bubble noise carries a significant amount of the total energy and masks the regulator signatures from 1.3 to 6 kHz, depending on the regulator configuration. While the dereverberation method is applied here to SCUBA signals, it is generally applicable to other sources if the impulse response of the recording environment can be obtained separately.

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Passive acoustic detection and classification of divers in harbor environments

Cited by 12 publications

References 5 publications

Structural Design and Test of a Piezoelectric Flextensional Transducer for Passive Detection of Frogmen

Structural Design and Test of a Piezoelectric Flextensional Transducer for Passive Detection of Frogmen

Classification of Surface Vehicle Propeller Cavitation Noise Using Spectrogram Processing in Combination with Convolution Neural Network

Partial dereverberation used to characterize open circuit scuba diver signatures

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