SONAR METHOD OF CLASSIFYING USING PSEUDONOISE SIGNAL Russian patent published in 2020 - IPC G01S15/00 

Abstract RU 2735929 C1

FIELD: acoustics.

SUBSTANCE: invention relates to the field of hydroacoustics. Method for classification using a pseudonoise signal in sonar comprises emitting a pseudonoise sounding signal, performing cross-correlation processing, determining the time position of the maximum of the cross-correlation function, determining the distance to the location object, determining the location object class, receiving the echo signal with a static fan of the directional characteristics, the maximums of which intersect at a level of not less than 0.7 of the maximum, mutually correlation processing is carried out between time implementations of adjacent spatial channels, by first time set determining threshold, determining the channel pair number for which the maximum of the cross-correlation function has the greatest amplitude, determining the time position of the maxima of the cross-correlation function, which exceed the threshold in the pairs of spatial channels adjacent to the pair of spatial channels, and if time positions coincide, then decision is made on presence of echo signal, distance to location object is determined, by number of selected spatial channels adjacent to pair of spatial channels, heading angle of location object is determined, and by their number - its angular length, the number of reflectors of the location object is determined from the number of maxima of the cross-correlation function, determining their time position and from the difference of time between the first and last maximum determining the radial extent of the location object, wherein the location object class is determined based on the obtained characteristics.

EFFECT: invention can be used to construct systems for automatic detection of echo signals received by a sonar with noise and reverberation noise, measurement of object parameters and classification thereof using pseudonoise signals.

1 cl, 1 dwg

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RU 2 735 929 C1

Authors

Timoshenkov Valerij Grigorevich

Dates

2020-11-10Published

2020-01-10Filed