Side lobe suppression method and array sparse method for multi-beam imaging sonar sparse array

Abstract

The invention discloses a side lobe suppression method and an array sparse method for a multi-beam imaging sonar sparse array. A sparse optimization problem of an array antenna is transformed into a linear regression problem of a sparse matrix, combination learning is carried out by taking the reconstruction of multiple beam direction patterns with different pointing directions as a target task, and a sparse semicircle array model for multi-task learning is established; based on the performance requirement of a preset main side lobe, a norm regular term of 1<1 / 2> of a weighted coefficient matrix is introduced on the basis of a least squares loss function, an iterative threshold converged method and an accelerating gradient descent method are used for solving an optimal weighting coefficient, and a weighting coefficient which minimizes a side lobe peak level is solved at the same time while optimizing the position of the sparse array. According to the side lobe suppression method and the array sparse method for the multi-beam imaging sonar sparse array, the problem that the sparse solution falls into the local optimum due to the mismatching of array position and weight vector is avoided, and peak side lobe levels of multiple beams formed by the array after sparseness is effectively reduced.

Description

technical field [0001] The invention belongs to the field of sonar signal processing, and in particular relates to a side lobe suppression method and an array sparse method of a multi-beam imaging sonar sparse array. Background technique [0002] An important indicator of imaging sonar is resolution, and higher resolution often requires imaging sonar to contain a large number of transducer arrays, and each array unit returns one receiving signal, which needs to be processed in parallel on the received multiple signals Pre-processing such as pre-amplification, TVG / AGC amplification, matched filtering, and acquisition has very high requirements on hardware circuit volume, FPGA resources, and power system power consumption. At the same time, large-scale array units require a large number of computing units and storage space when performing multi-beamforming. In order to solve the above problems, the study of sparse arrays came into being. [0003] Sparse array is a kind of ar...

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Problems solved by technology

[0004] In order to solve the technical problems raised by the above-mentioned background technology, the present invention aims to provide a sidelobe suppression method and an array sparse method for multi-beam imaging sonar sparse arrays, so as to avoid the main target of sonar detection from being unable to move from the messy ones caused by the lifting of the beam sidelobes. Issues with resolution in background images

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