【摘要】 提出一种使用协方差矩阵分解(CMD)的声矢量阵声压振速联合处理方法。该方法将声压振速互协方差矩阵分解为观测方位系数矩阵和剩余协方差矩阵,将系数矩阵与导向矢量结合避免了观测方位的选择,对剩余协方差矩阵进行奇异值分解并重构厄米特协方差矩阵,最后对重构的协方差矩阵实施最小方差无失真响应(MVDR)方法处理。理论分析表明,使用重构的协方差矩阵能够获得更高的阵处理增益。数值仿真结果验证了本文方法的计算量与Nehorai处理方法相近,但较传统声压振速联合处理方法具有更高的阵处理增益和目标分辨能力。更多还原

【Abstract】 A combined processing method of pressure and particle velocity(PV-CPM) for acoustic vector sensor array using covariance matrix decomposition(CMD) is proposed. In this method, the cross-covariance matrix of pressure and particle velocity is decomposed into an observation angle coefficient matrix and a residual covariance matrix. To avoid choosing the observation angle,the coefficient matrix is combined with the guidance vector. By adopting the singular value decomposition, the residual covariance matrix is reconstructed into the new Hermitian covariance matrix, which is ultimately used to implement the MVDR beamforming method. Theoretical analysis shows that the new covariance matrix can achieve higher array processing gain. Furthermore, the numerical simulation proves that the computational complexity of the proposed method is similar to that of the Nehorai’s method, but its array processing gain and multi-target resolution are higher than those of the traditional PV-CPM.更多还原