Second-order statistics-based multi-parameter estimation of near-field acoustic sources

被引:0
|
作者
Li Xinbo [1 ]
Liu Nannan [1 ]
Jiang Nan [1 ]
Long Xiaobo [1 ]
Jiao Xiaoyang [2 ]
机构
[1] Jilin Univ, Sch Commun Engn, Changchun 130025, Peoples R China
[2] Jilin Univ, Sch Mech Engn, Changchun 130025, Peoples R China
来源
关键词
Acoustic vector-sensor array; Near-field source; DOA estimate; Range estimate; Second -order Statistics; VECTOR-SENSOR ARRAY;
D O I
10.4028/www.scientific.net/AMM.461.977
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
In this paper, a new approach based on the second-order statistics (SOS) and acoustic vector sensor (AVS) array is proposed, for localization estimation of near-field acoustic narrowband sources. Firstly, we choose the centrosymmetric uniform linear-array as the AVS arrangement, and the array is consistent with the coordinate axis direction of the acoustic vector-sensor. This estimation method makes good use of the acquisition information from the AVS, such as one-dimensional sound pressure and three-dimensional particle velocity, and has shown preferable performance for the parameter estimation of direction-of-arrival (DOA) and range of target acoustic sources in the near field. The estimation algorithm expands the near-field array manifold of one single acoustic vector sensor to the acoustic vector-sensor's uniform linear-array, and the near-field acoustic vector sensor linear array output model is deduced. The autocorrelation and cross-correlation function of the velocity field and the pressure field are used to construct the rotational invariance frame, which helps to extract the expected information. Consequently, the closed-form solutions of the incident source's DOA and range are derived explicitly through the parameter pairing operation. The proposed method reduces the computational burden and has good spatial recognition ability and high resolution in the case of limited array elements. It also has better engineering application prospect. Eventually, the performance of the method is verified by Monte Carlo simulation experiments.
引用
收藏
页码:977 / +
页数:3
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