Wideband MVDR beamforming for acoustic vector sensor linear array

2004 ◽  
Vol 151 (3) ◽  
pp. 158 ◽  
Author(s):  
H.-W. Chen ◽  
J.-W. Zhao
Keyword(s):  
Linear Array ◽  
Acoustic Vector Sensor ◽  
Vector Sensor ◽  
Mvdr Beamforming

Second-Order Statistics-Based Multi-Parameter Estimation of Near-Field Acoustic Sources

2013 ◽  
Vol 461 ◽  
pp. 977-983
Author(s):  
Xin Bo Li ◽  
Nan Nan Liu ◽  
Nan Jiang ◽  
Xiao Bo Long ◽  
Xiao Yang Jiao
Keyword(s):  
Parameter Estimation ◽  
Order Statistics ◽  
Linear Array ◽  
Near Field ◽  
Second Order ◽  
Uniform Linear Array ◽  
Acoustic Vector Sensor ◽  
Second Order Statistics ◽  
Vector Sensor ◽  
Acoustic Sources

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.

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