目标方位估计(Direction of arrival,DOA)和信号恢复分别是水下目标定位、跟踪与识别的前提.基于盲源分离方法可以得到含有阵列流形信息的解混矩阵,融合成熟的高分辨方法提出了一种新的方位估计、信号恢复模型和方法.在宽带信号背景下...目标方位估计(Direction of arrival,DOA)和信号恢复分别是水下目标定位、跟踪与识别的前提.基于盲源分离方法可以得到含有阵列流形信息的解混矩阵,融合成熟的高分辨方法提出了一种新的方位估计、信号恢复模型和方法.在宽带信号背景下进行了仿真实验,结果表明该方法可实现目标方位的实时估计和目标信号的恢复.在同等条件下完成同样的目标方位分辨率,比单纯的高分辨方法要求的阵元数和快拍数较少,要求的信噪比要低.海上实测数据检验也表明,比常规的最小方差无失真响应(Minimum variance distortionless response,MVDR)方法得到了更好的结果,明显提高了弱目标信号的空间谱能量,增强了检测弱目标信号的能力.展开更多
To improve localization accuracy, the spherical microphone arrays are used to capture high-order wavefield in- formation. For the far field sound sources, the array signal model is constructed based on plane wave deco...To improve localization accuracy, the spherical microphone arrays are used to capture high-order wavefield in- formation. For the far field sound sources, the array signal model is constructed based on plane wave decomposition. The spatial spectrum function is calculated by minimum variance distortionless response （MVDR） to scan the three-dimensional space. The peak values of the spectrum function correspond to the directions of multiple sound sources. A diagonal loading method is adopted to solve the ill-conditioned cross spectrum matrix of the received signals. The loading level depends on the alleviation of the ill-condition of the matrix and the accuracy of the inverse calculation. Compared with plane wave decomposition method, our proposed localization algorithm can acquire high spatial resolution and better estimation for multiple sound source directions, especially in low signal to noise ratio （SNR）.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No.61001160)the Doctoral Foundation of Ministry of Education (Grant No.20093108120018)the Shanghai Leading Academic Discipline Project (Grant No.S30108)
文摘To improve localization accuracy, the spherical microphone arrays are used to capture high-order wavefield in- formation. For the far field sound sources, the array signal model is constructed based on plane wave decomposition. The spatial spectrum function is calculated by minimum variance distortionless response （MVDR） to scan the three-dimensional space. The peak values of the spectrum function correspond to the directions of multiple sound sources. A diagonal loading method is adopted to solve the ill-conditioned cross spectrum matrix of the received signals. The loading level depends on the alleviation of the ill-condition of the matrix and the accuracy of the inverse calculation. Compared with plane wave decomposition method, our proposed localization algorithm can acquire high spatial resolution and better estimation for multiple sound source directions, especially in low signal to noise ratio （SNR）.
