Array optimization of sparse regularization equivalent source acoustic holography algorithm

Hantao Chen,Jing Xia,Wenyong Guo,Jianggui Han

doi:10.21595/jve.2021.21659

Hantao Chen, Jing Xia + Show 2 more

Open Access

https://doi.org/10.21595/jve.2021.21659

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Abstract

In order to improve the accuracy of the sparse regularization equivalent source acoustic holography algorithm, based on the analysis of the holographic algorithm theory, an optimized array arrangement is proposed. The sensing matrix constructed by the array parameters directly affects the accuracy of the acoustic imaging algorithm. By analyzing the influence of the sensing matrix on the imaging algorithm, the Restricted Isometry Constant (RIC) is chosen to evaluate the sensing matrix. Using genetic algorithm (GA), the RIC is taken as the fitness value, and the optimal pseudo-random array is selected and compared with the conventional array arrangement for acoustic imaging. Experiments show that the optimized pseudo-random array has better imaging effect under the same number of sensor measurements, and provides an optimization method for the design of acoustic array.

Highlights

According to the properties, waves can be divided into mechanical waves, electromagnetic waves, gravitational waves and matter waves, Scholars have carried out research on different types of waves [1,2,3,4,5,6]
In order to ensure the accuracy of acoustic source localization by using this technique, the sensing matrix is required to meet the Restricted Isometry Property (RIP) and Mutual Incoherence Property (MIP) [11]
Based on a deep understanding of the principle of sparse regularization, this paper first briefly introduces the mathematical model of the sparse regularization equivalent source acoustic holography method, and discusses that the constraint of RIP and MIP conditions on the sensor matrix is an important prerequisite to ensure the signal sparse reconstruction

Summary

Introduction

Waves can be divided into mechanical waves, electromagnetic waves, gravitational waves and matter waves, Scholars have carried out research on different types of waves [1,2,3,4,5,6]. ARRAY OPTIMIZATION OF SPARSE REGULARIZATION EQUIVALENT SOURCE ACOUSTIC HOLOGRAPHY ALGORITHM. This shows that a suitable array can be obtained by numerical optimization. Based on a deep understanding of the principle of sparse regularization, this paper first briefly introduces the mathematical model of the sparse regularization equivalent source acoustic holography method, and discusses that the constraint of RIP and MIP conditions on the sensor matrix is an important prerequisite to ensure the signal sparse reconstruction. The performance of the optimized array is analyzed by comparing the optimized array arrangement with the traditional square array and circular array in simulation experiment

Mathematical model of acoustic imaging algorithm

Measurement of incoherence of the sensing matrix

Optimization of array design

Array parameters

Establishment of simulation model

Conclusions