1. Array optimization of sparse regularization equivalent source acoustic holography algorithm
- Author
-
Wenyong Guo, Jianggui Han, Jing Xia, and Hantao Chen
- Subjects
Holographic algorithm ,Computer science ,Mechanical Engineering ,Monte Carlo method ,02 engineering and technology ,Acoustic holography ,Isometry (Riemannian geometry) ,01 natural sciences ,Matrix (mathematics) ,array optimization ,020303 mechanical engineering & transports ,0203 mechanical engineering ,sensing matrix ,0103 physical sciences ,Genetic algorithm ,TJ1-1570 ,General Materials Science ,Mechanical engineering and machinery ,equivalent source acoustic holography ,Sparse regularization ,Constant (mathematics) ,monte-carlo method ,010301 acoustics ,Algorithm - 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.
- Published
- 2021