A Partition Spatial Filtering Method for Acoustic Array Configuration
Author(s) -
Zhihong Liu,
Xilong Zhang,
Zunmin Liu,
Chuijie Yi,
Ming Ma
Publication year - 2021
Publication title -
shock and vibration
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 45
eISSN - 1875-9203
pISSN - 1070-9622
DOI - 10.1155/2021/6682923
Subject(s) - microphone array , computation , circular buffer , sparse array , partition (number theory) , spatial filter , acoustics , computer science , microphone , bandwidth (computing) , sensor array , array data structure , grid , doppler effect , algorithm , mathematics , physics , loudspeaker , telecommunications , geometry , artificial intelligence , combinatorics , astronomy , machine learning , programming language
Acoustic array is a ubiquitous tool for locating and quantifying sound sources. However, its effectiveness depends greatly on the array configuration. This paper presents an array configuration method to enhance array performance, especially on the spatial resolution and the Doppler effect correction. The problem of array configuration is formulated into a position matrix determined by introducing partition spatial filtering. Irregular coaxial ring grid spacings and partition filtering conditions are suggested to control array spatial resolution. Geometrical parameters and performance indicators are constructed to quantify the relationships between the array configuration and performance. Based on these quantitative relations, the spatial variation of the array beam pattern and the Doppler effect has got adaptive adjustment. In particular, an adaptive partition algorithm is proposed to reduce computation time. The performance of the method is examined numerically and experimentally, which is compared with the other methods. The results provide the method to guide the design of a 64-microphone optimized array with high performance (1.8° spatial angle resolution and 40% Doppler frequency correction over the bandwidth from 800 Hz to 3000 Hz) and fast computing speed (18 s array generated time for 2000 arrays). Furthermore, an unusual feature of the method is that it can be utilized in the case when the source moves at a nonconstant velocity.
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