研究了矢量水听器阵利用旋转不变子空间(estimation of signal parameters via rotational invariance technique,ESPRIT)算法估计目标方位的问题,分析了几种处理方式的内在机理,并推导了它们的理论误差公式。针对利用振速分量直接估计方位受声源方位影响较大的问题,提出了一种角度融合的方法来提高方位估计性能。仿真结果表明,理论误差与实际非常吻合,提出的优化融合处理方法提高了目标方位估计的精度,降低了估计误差随方位角度变化波动的程度。
针对水声传感器网络高能耗的特点，该文提出了基于空间唤醒的节能路由协议ERBSW（Energy-efficient Routing protocol Based on Spatial Wakeup），该协议将3维网络空间划分为唤醒层和睡眠层，每个节点根据当前的深度信息，动态地决定其处于唤醒或睡眠状态。另外，ERBSW通过定期地广播Hello包来建立唤醒邻节点集合，使得数据包由较高的唤醒层节点向较低的唤醒层节点传递，从而避免了冗余节点因空闲侦听以及不必要的数据接收所产生的能量浪费。仿真结果表明，在不同网络密度条件下，该协议相比VBF（Vector—Based Forwarding）能耗节省了约16％～48％。
A multiple targets detection method based on spatial smoothing (MTDSS) is proposed to solve the problem of the source number estimation under the colored noise background. The forward and backward smoothing based on auxiliary vectors which are received data on some specific elements is computed. By the spatial smoothing with auxiliary vectors, the correlated signals are decorrelated, and the colored noise is partially alleviated. The correlation matrix formed from the cross correlations between subarray data and auxiliary vectors is computed. By exploring the second-order statistics property of the covariance matrix, a threshold based on Gerschgorin radii of the smoothing correlation matrix is set to estimate the number of sources. Simulations and experimental results validate that MTDSS has an effective performance under the condition of the colored noise background and coherent sources, and MTDSS is robust with the correlated factor of signals and noise.
