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Development of a 3-D Bioacoustic Imaging System

Development of a 3-D Bioacoustic Imaging System
3D 生物声学成像系统的开发
批准号:
8914300
负责人:
Jules Jaffe
金额:
$69.32万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1990
资助国家:
美国
项目状态:
已结题
起止时间:
1990-06-01 至 1995-02-28

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中文摘要
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英文摘要
The Marine Physical Laboratory at Scripps Institution of Oceanography will develop a sea-going, three-dimensional bioacoustic imaging system. The system addresses a long- standing requirement within biological oceanography to describe the distribution and interactions of small plank- tonic organisms in the open ocean. The use of nets and other acoustic devices are often inadequate in describing the distribution of organisms in certain scientifically important spatial and temporal scales. The imaging system is based on the principle of Spatially Variant Insonification, whereby spatial resolution in the water column relies on simultaneous transmission of discrete coded pulses along narrow acoustic beams. The reflection of these acoustic pulses, that are received at a single transducer, can then be deciphered from each other and an image is produced by complex mathematical processing. The system will operate at 500 kHz and will be designed to have a useful range of 50 meters within a 30- degree solid angle. At this frequency, the instrument will be sensitive to zooplankton and will be used to map and follow the distribution of these small organisms. A 3-D bioacoustic imaging capability will be useful to a number of envisioned research projects over the next decade. The new capability will provide information on the interactions and movements of the organisms within a volume of water.
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EAGER: ATMARS, an AuTonomous underwater vehicle with ancillary optics to measure MARine Snow size, concentration, and descent rate.
Collaborative Research: Development of a Swarm of Autonomous Subsea Vehicles to Infer Plankton Growth and Transport
A Benthic Underwater Microscope with Pulse Amplitude Modulated Imaging Capability (BUMP)
BIGDATA: Collaborative Research: IA: Quantifying Plankton Diversity with Taxonomy and Attribute Based Classifiers of Underwater Microscope Images
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