METHOD FOR DETECTING LOCAL OBJECT AGAINST BACKGROUND OF DISTRIBUTED INTERFERENCE Russian patent published in 2020 - IPC G01S15/04 G01S7/537 G01S7/539 

Abstract RU 2736097 C1

FIELD: hydro acoustics.

SUBSTANCE: invention relates to the field of hydroacoustics and can be used for construction of local object detection systems in conditions of distributed interference of various origin. Method of detecting a local object comprises emitting a complex probing signal, receiving an echo signal with a multichannel receiving path, spatial receiving channels of which form a fan of static directional characteristics crossing at a level, not less than 0.7 of the maximum, a set of time realizations in each receiving channel, having the same time of arrival of the signal, determination of correlation connection between adjacent receiving channels. In each time realization of each receiving channel, the spectrum of the received signal is calculated, determining in each receiving channel a module of mutually-covariance function of the received and emitted signals by inverse Fourier transform of convolution of the echo signal spectrum with a complex conjugate spectrum of the emitted signal. Correlation of envelopes of temporal realizations of neighbouring receiving channels is determined by finding maximum modulus of mutually covariance function between envelopes of reflections of space volume in neighbouring receiving channels. Further, average value is determined by all maxima, all maxima of mutually-covariance functions are normalized to average value. Decision on the presence of a local object is taken if the normalized maxima of mutually-covariance functions of the level of the selected threshold are exceeded in not more than N receiving channels, otherwise a decision is made to detect a non-local object.

EFFECT: technical result is high noise immunity of detecting local objects in conditions of intense reverberation interference and low level of echo signal with multiple-field structure of object.

1 cl, 3 dwg

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RU 2 736 097 C1

Authors

Makarov Nikolaj Aleksandrovich

Kulakov Anton Khakimovich

Dates

2020-11-11Published

2019-12-30Filed