一种改进的UWSAN最大似然目标定位方法

研究水声信道目标定位问题,由于水下定位精度与陆地不同。为了解决水下水声信道中有效传输信息,采用传统的无线传感器阵列网络(UWSAN)最大似然目标定位方法有效性差。为解决上述问题,提出将每个阵列的局域似然函数进行信息提取和压缩,并将信息进行融合。分析每个阵列的局域似然函数特性,并根据高斯函数对归一化似然函数进行拟合,结合各个阵列接收到的能量,在融合时先给拟合的归一化似然函数乘以其接收到的能量,再将各个阵列的对数似然函数相加得到全局对数似然函数,其中最大值的位置就是最大似然法估计的目标位置。数值仿真结果表明,改进方法不但大大降低了局部节点到融合节点的传输数据量,而且在高信噪比下与直接计算似然函数的数值非常接近,可以有效估计目标的位置。

Target Localization Method Based Maximum Likelihood in UWSAN

For obtaining the global logarithm likelihood function,all the received data have to be transmitted to the fusion center in Underwater Wireless Sensor Array Network(UWSAN).However,the bandwidth of wireless communication is limited in it.In order to solve this problem,the modeling and fitting of local logarithm likelihood function were focused on in this paper.According to the characteristics of likelihood function,Gaussian function was selected as the basis function in least-square fitting.Preliminary numerical simulation results show that this method can guarantee likelihood function with an unchanged key performance,greatly reduce the quantity of the transmission data from local nodes to fusion nodes,and has a better performance in target localization.