Abstract
In this paper, the issue of direction of arrival (DOA) estimation is discussed, and a partial angular sparse representation (SR)-based method using a sparse separate nested acoustic vector sensor (SSN-AVS) array is developed. Traditional AVS array is improved by separating the pressure sensor array and velocity sensor array into two different sparse array geometries with nested relationship. This improved array geometry can achieve large degrees of freedom (DOF) after the extended vectorization of the cross-covariance matrix, and only partial SR of the angle is required by exploiting the cyclic phase ambiguity caused by the large inter-element spacing of the virtual array. Joint sparse recovery is developed to amend the grid offset and unitary transformation is utilized to transform the complex atoms into real-valued ones. After sparse recovery, the sparse vector can simultaneously provide high-resolution but ambiguous angle estimation and unambiguous reference angle estimation embedded in the AVS array, and they are combined to obtain unique and high-resolution DOA estimation. Compared to other state-of-the-art DOA estimation methods using the AVS array, the proposed algorithm can provide better DOA estimation performance while requiring lower complexity. Multiple simulation results verify the effectiveness of the approach.
Highlights
Sensor arrays can utilize signals from multiple paths to overcome fading effect and enhance system capacity, so they have found wide application in many fields [1,2,3,4]
We propose a sparse separate nested (SSN) acoustic vector sensor (AVS) array, which separates the pressure sensor array and velocity sensor array into two different geometries, which have a nested relationship, while both have large inter-element spacing
We propose an sparse separate nested acoustic vector sensor (SSN-AVS) array shown in Figure 1b, where the pressure sensors extracted and arranged along negative side with inter-element spacing being sensors areare extracted and arranged along thethe negative side with inter-element spacing being
Summary
Sensor arrays can utilize signals from multiple paths to overcome fading effect and enhance system capacity, so they have found wide application in many fields [1,2,3,4]. In [26], we separated the pressure sensor array and velocity sensor array in the AVS array into two nested geometries, generating high DOFs in the co-array domain, but sparse representation (SR) covering the whole angular range is required. Both the methods in [25,26] assume the sources are correctly located in the predefined grid, which cannot be guaranteed, no matter how fine the grid is [27]. IK and IIK are K × K identity matrix and reverse identity matrix, respectively. ./ means element-wise division, and angle(.) means to extract the phase
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