Combined algorithms for detection of acoustic categories
MetadataShow full item record
Original versionThis report is not to be cited without prior reference to the authors
There is a current desire to harvest marine resources by managing total marine ecosystems rather than single species of the ecosystems. By means of algorithms applied on high-quality multi-frequency acoustic data, species, or rather acoustic categories, of the ecosystem can be identified. This information may significantly increase the accuracy of acoustic survey estimates of fish and to some extent also for zooplankton. Multi-frequency split beam echo sounders with nearly identical and overlapping acoustic beams have been regularly used in acoustic surveys for fish stock abundance estimation at Institute of Marine Research for the last five years. Calibrated raw data from up to six simultaneously working echo sounders at 18, 38, 70, 120, 200 and 364 kHz was used as input to a stepwise, modular sequence of analysis, like bottom detection, noise quantification and removal, target categorisation and school detection in near real-time. Direct generation of new, synthetic echograms, based upon the measured or modelled relative frequency response of the targets is one of the most useful features of the systems. The result of the categorisation process can be used to show the spatial distribution of different acoustic categories in a single synthetic echogram, or to keep some and remove other acoustic categories in echograms at a single frequency.