Sonar discrimination of cylinders from different angles using neural networks neural networks

This paper describes an underwater object discrimination system applied to recognize cylinders of various compositions from different angles. The system is based on a new combination of simulated dolphin clicks, simulated auditory filters and artificial neural networks. The model demonstrates its potential on real data collected from four different cylinders in an environment where the angles were controlled in order to evaluate the models capabilities to recognize cylinders independent of angles. 1. INTRODUCTION Dolphins possess an excellent sonar system for solving underwater target discrimination and recognition tasks in shallow water (see e.g., [2]). This has inspired research in new sonar systems based on biological knowledge, i.e. modeling the dolphins discrimination capabilities (see e.g., [4] and [5]). The fact that the inner ear of the dolphin has many similarities with the human inner ear makes it tempting to use knowledge from simulations of the human auditory system when t..

Low Energy, Passive Acoustic Sensing for Wireless Underwater Monitoring Networks

Ph. D. ThesisThis thesis presents the research conducted to develop low energy passive acoustic monitoring (PAM) algorithms. There are many signal processing techniques and machine learning systems which are capable of detecting and classifying target signals. However, this project aims to produce PAM detection and classification results using a low energy budget. The benefit of using this approach is that physical devices can be developed and deployed in open sea for several months using only battery power. This opens up the deployment area to very deep water where power sources are not readily available. Using passive acoustic communication to relay the detection data produced by the algorithm, it is expected that these systems could form an underwater network of sensor nodes. There are three targets for passive acoustic detection/classification included in this thesis, which are motorised surface vessels, cetacean clicks and cetacean whistles. The surface vessel detection method is based on a low energy implementation of Detection of Envelope Modulation On Noise (DEMON). Vessels produce high frequency modulated noise during propeller cavitation which the DEMON method aims to extract for the purposes of automated detection. The vessel detector design has different approaches with mixtures of analogue and digital processing, continuous and duty-cycled sampling/processing. The detector has been integrated with a low cost/power acoustic modem platform to provide acoustic communication of data in near real time. The vessel detector has been deployed at 20m depth for a total of 84 days in the North Sea providing a large data set, which the results are based on. Open sea field trial results have shown the detection of single and multiple vessels with a 94% corroboration rate with local Automatic Identification System (AIS) data. Results have shown additional information about the detected vessel, such as the number of propeller blades, can been extracted solely based on the detection data. The attention to energy efficiency has led to an average power consumption of 11.4mW enabling long term deployments of up to 6 months using only four alkaline C cells. Additional battery packs and a modified enclosure could enable a longer deployment duration. As the detector was still deployed during the first UK lockdown, the impact of Covid-19 on North Sea fishing activity has been captured in the results. Cetacean click detection is based on identifying and classifying the high frequency impulsive click trains created by cetaceans during navigation and foraging. A low energy method of detecting these vocalisations is proposed alongside a statistical based method of classification. The algorithm developed was tested using real recordings of cetacean activity and comparisons have been conducted against a commercially available cetacean monitoring system. The results show that the energy efficient algorithm produces comparable results to the commercial system when real recordings are processed. The cetacean whistle detection algorithm is based on a low energy phase locked loop (PLL) technique. PLL methodology has been adapted for this project to aid in developing a low energy approach to detecting cetacean whistles by tracking the sweeps in frequency they produce. Results are based on offline processing using real recordings of these animals. The results have shown a 75% success rate when comparing against human analysis of the recording. Future work includes the further development of the cetacean related algorithms into fully deployable, battery-powered, nodes for open sea field trails. The future work related to vessel detection includes adding a tracking feature to the passive acoustic monitoring technology.Engineering and Physical Sciences Research Council (EPSRC

Objekterkennung durch Echoortung und der Einfluß zeitlicher Integrationsmechanismen bei der Fledermaus Megaderma lyra

Diese Arbeit befaßt sich mit der Objekterkennung durch Echoortung bei der Fledermaus Megaderma lyra und zeigt welche Rolle hierbei die zeitliche Integration akustischer Information spielt. Es werden zwei psychoakustische Experimente beschrieben, deren Ergebnisse mit adäquaten Modellen verglichen werden und somit einen Einblick in die Verarbeitungsmechanismen des auditorischen Systems von M. lyra gewähren. Das erste Experiment untersucht die Objekterkennung durch Echoortung anhand der spontanen Klassifizierung unbekannter virtueller Objekte im Rückspielexperiment. Hierbei ist von Interesse, welche Klassifizierungsstrategie bei der Objekterkennung Anwendung findet. Bewertet M. lyra Objekte durch den Vergleich unterschiedlicher Objektechos oder ist sie fähig das akustische Abbild eines Objektes durch eine Kreuzkorrelation ihres Lautes mit dem Objektecho zu extrahieren? Der Vergleich der Ergebnisse aus dem Verhaltensexperiment mit der Klassifizierung der Testobjekte durch unterschiedliche Modelle weist darauf hin, daß M. lyra tatsächlich die Fähigkeit besitzt, das akustische Abbild unbekannter Objekte zu extrahieren. Zudem zeigt der Vergleich mit der Klassifizierung durch ein auditorisches Modell, daß die Echoinformation von Objekten kleiner als 6,6 cm im peripheren auditorischen System spektral kodiert wird. Die Ergebnisse einer begleitenden Analyse der Echoortungslaute während des Verhaltensexperiments deuten darauf hin, daß M. lyra ihr Echoortungsverhalten zur spontanen Klassifizierung unbekannter Objekte nicht adaptiv verändert, sondern in gleicher Weise einsetzt wie bei der Klassifizierung bekannter Objekte. Das zweite Projekt befaßt sich mit den Einflüssen zeitlicher Verarbeitungsmechanismen auf die Echoabbildung. Hierzu wird die zeitliche Integration akustischer Information in Abhängigkeit des zeitlichen Abstandes zweier Schallereignisse sowohl unter passiv-akustischen Bedingungen als auch im Echoortungskontext untersucht. Unter beiden Bedingungen können bei M. lyra gleichermaßen kurze Integrationszeiten von weniger als 200 µs beobachtet werden. Der Vergleich der Ergebnisse aus dem Verhaltensexperiment mit einem auditorischen Modell der Gehörperipherie von M. lyra zeigt, daß die zeitliche Integration kurzer Signalpaare anhand der Überlappung cochleärer Filterantworten erklärt werden kann. Demnach kann das periphere auditorische System von M. lyra Objektstrukturen von weniger als 3,4 cm nicht zeitlich auflösen und somit nur spektral kodieren. Objektstrukturen von mehr als 3,4 cm könnten hingegen zeitlich aufgelöst und somit zeitlich kodiert werden. Wie die Ergebnisse des ersten Experiments zeigen, wird jedoch die akustische Information von Objekten bis zu 6,6 cm peripher rein spektral kodiert und die zeitliche Information nicht genutzt

Underwater object localization using a biomimetic binaural sonar

Thesis (S.M. in Oceanographic Engineering)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Ocean Engineering; and the Woods Hole Oceanographic Institution), 1999.Includes bibliographical references (leaves 85-89).by Qiang Wang.S.M.in Oceanographic Engineerin

Sonar systems for object recognition

The deep sea exploration and exploitation is one of the biggest challenges of the next century. Military, oil & gas, o shore wind farming, underwater mining, oceanography are some of the actors interested in this eld. The engineering and technical challenges to perform any tasks underwater are great but the most crucial element in any underwater systems has to be the sensors. In air numerous sensor systems have been developed: optic cameras, laser scanner or radar systems. Unfortunately electro magnetic waves propagate poorly in water, therefore acoustic sensors are a much preferred tool then optical ones. This thesis is dedicated to the study of the present and the future of acoustic sensors for detection, identi cation or survey. We will explore several sonar con gurations and designs and their corresponding models for target scattering. We will show that object echoes can contain essential information concerning its structure and/or composition

Passive acoustic tracking of divers and dolphins

This thesis describes work performed in the analysis and development of positioning algorithms for self-noise of a known kind; it also describes the development of short base-line systems capable of positioning the sources. Many studies of wild cetaceans rely on tracking the movement of wild animals, often in hostile conditions and with limited contact with these animals. Advanced technology exists for satellite or radio tracking of marine wildlife, but this relies on an animal being first caught and tagged. In situations where random interactions with marine wildlife are to be analysed, it is not practicable to attach devices to an animal, so it is appropriate to use passive techniques, in which the animal's self noise is located and tracked. Present passive systems usually include a long base-line array, which can be difficult to deploy. The problem may be overcome by reducing the array in size, but it results in an increase in positioning errors. This study attempts to quantifY these errors and looks into the practicability of short base-line passive arrays. Two systems are described here, both for tracking impulsive sounds in real time. The first is for use on pelagic trawl nets, the other as a prototype high-speed system to prove the different algorithms developed before and during this study. The prototype systems, each having a minimum of four receivers positioned in various configurations, have been tested in a tank with a controlled sound source. The source is a 'pinger', which allows the systems also to be adopted for diver positioning and tracking. A survey of unclassified literature has shown characteristics of cetacean acoustic signatures, which have been utilised in the optimisation of the systems. The physiology of cetaceans has also been reviewed to help understand the physical limitations of the systems presented.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

1995 BRAC Commission

Data Call - Naval Command, Control and Ocean Surveillance Center, Research Development Test Evaluation Division - San Diego, CA. Data Call #5. Box 186, L-118