Passive acoustic methods of small boat detection, tracking and classification

Pollara, Alexander; Sutin, Alexander; Salloum, Hady

doi:10.1109/ths.2017.7943488

Cited by 12 publications

(9 citation statements)

References 17 publications

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“…Monitoring the general increase of boating activity can take advantage from PAM allied to automatic recognition methods, especially if focussed on private boats not required to use AIS (Automated Identification System). In fact, in contrast with large scale fishing vessels that are monitored though the Vessel Monitoring System (VMS), the presence of small boats may be difficult to monitor (Pollara et al, 2017) since they are usually not equipped with AIS and, due to their size, they are not generally well detected by radar.…”

Section: Comparison Between öResund Strait (Sweden) and Tagus Estuary (Portugal)mentioning

confidence: 99%

Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models

Vieira

Amorim

Sundelöf

et al. 2019

ICES Journal of Marine Science

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Passive acoustic monitoring (PAM) is emerging as a cost-effective non-intrusive method to monitor the health and biodiversity of marine habitats, including the impacts of anthropogenic noise on marine organisms. When long PAM recordings are to be analysed, automatic recognition and identification processes are invaluable tools to extract the relevant information. We propose a pattern recognition methodology based on hidden Markov models (HMMs) for the detection and recognition of acoustic signals from marine vessels passages and test it in two different regions, the Tagus estuary in Portugal and the Öresund strait in the Baltic Sea. Results show that the combination of HMMs with PAM provides a powerful tool to monitor the presence of marine vessels and discriminate different vessels such as small boats, ferries, and large ships. Improvements to enhance the capability to discriminate different types of small recreational boats are discussed.

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Section: Comparison Between öResund Strait (Sweden) and Tagus Estuary (Portugal)mentioning

confidence: 99%

Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models

Vieira

Amorim

Sundelöf

et al. 2019

ICES Journal of Marine Science

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“…Work according to [3]: latent acoustic ways will discover, trace and order surface and submerged vessels. Authors described review of arranged methods of recognition and pursuit for affordable and economical power-consuming frameworks.…”

Section: Literature Surveymentioning

confidence: 99%

A Model for Boat Accident Prediction Using Geographical and Topological Data

et al. 2021

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In recent years, natural calamities and disasters have inflated day by day and people have suffered the results of them. One of the foremost reasons being, lack of correct data which can be reached to individuals. Google Maps is growing speedily within the world, attributable to the supply of geospatial data. It is also because of the increase in devices which will benefit from such data, specifically, Global Positioning System (GPS) enabled devices. The catholicity of hand-held computing devices has been found to be particularly economical and effective in conducting disaster management and relief operations. Thus the associate application is in want which may alert users once there is a stroke of natural bad luck in their section. By knowing beforehand, the users of that application will take acceptable measures to avoid wasting themselves and scale back the dependence on search and rescue groups. Throughout this process there is a stroke of bad luck and results of their experiences may be used elsewhere for providing alerts. Such associate application eliminates the necessity for rescue since the users are supplied with alerts if they are in a very bad luck zone. Thus users may be tuned in to the danger they're in and take necessary measures. APSDMA (Andhra Pradesh State Disaster Management Authority) is making an attempt to help the individuals by providing the information of the natural disaster at a selected space and alert the individuals at the particular space. In-order to provide such alert information, APSDMA needs a platform. This paper presents the Webpage that is developed with the requirements given by APSDMA for the day to day actions.

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“…The process for extracting these features is the detection of envelope modulation on noise (DEMON) algorithm. This process has been demonstrated successfully on small boats [45,46] and ships [44] for the purpose of small vessel DCLT in ports and harbors.…”

Section: Discussionmentioning

confidence: 99%

“…Another application of passive sonar in national security is classifying which vessels are authorized to navigate in marine protected areas and monitoring harbor traffic for maritime law enforcement. Small boats are difficult to detect above water with radar, [46] and optical methods are limited by weather for visibility [113,131]. In addition to filling the gaps of these remote sensing methods, passive sonar is inherently covert, which is essential in defense applications.…”

Section: Discussionmentioning

confidence: 99%

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Advances in passive acoustic detection, localization, and tracking applied to unmanned underwater vehicles

Kita¹

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Detection, classification, localization, and tracking (DCLT) of unmanned underwater vehicles (UUVs) in the presence of shipping traffic is a critical task for passive acoustic harbor security systems. In general, vessels can be tracked by their unique acoustic signature due to machinery vibration and cavitation noise. However, cavitation noise of UUVs is considerably quieter than ships and boats, making detection significantly more challenging. In this thesis, I demonstrated that it is possible to passively track a UUV from its highfrequency motor noise using a stationary array in shallow-water experiments with passing boats. First, causes of high frequency tones were determined through direct measurements of two UUVs at a range of speeds. From this analysis, common and dominant features of noise were established: strong tones at the motor’s pulse-width modulated frequency and its harmonics. From the unique acoustic signature of the motor, I derived a high-precision, remote sensing method for estimating propeller rotation rate. In shallow-water UUV field experiments, I demonstrated that detecting a UUV from motor noise, in comparison to broadband noise from the vehicle, reduces false alarms from 45% to 8.4% for 90% true detections. Beamforming on the motor noise, in comparison to broadband noise, improved the bearing accuracy by a factor of 3.2×. Because the signal is also high-frequency, the Doppler effect on motor noise is observable and I demonstrate that range rate can be measured. Furthermore, measuring motor noise was a superior method to the “detection of envelope modulation on noise” algorithm for estimating the propeller rotation rate. Extrapolating multiple measurements from the motor signature is significant because Bearing-Doppler-RPM measurements outperform traditional bearing-Doppler target motion analysis. In the unscented Kalman filter implementation, the tracking solution accuracy for bearing, bearing rate, range, and range rate improved by a factor 2.2×, 15.8×, 3.1×, and 6.2× respectively. These findings are significant for improving UUV localization and tracking, and for informing the next-generation of quiet UUV propulsion systems.

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Passive acoustic methods of small boat detection, tracking and classification

Cited by 12 publications

References 17 publications

Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models

Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models

A Model for Boat Accident Prediction Using Geographical and Topological Data

Advances in passive acoustic detection, localization, and tracking applied to unmanned underwater vehicles

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