极大似然估计的信息融合方法及其在水下航行器制导中的应用

对基于极大似然估计的数据融合技术进行了理论分析，证明了用多传感器融合估计后的数据较单传感器测量数据方差减小；并把该技术应用于水下航行器制导技术，对其进行了理论分析，提出了一种新的航行器制导技术，最后对该技术应用于航行器制导和目标跟踪技术进行了仿真计算，结果证明了该方法的有效性。

On Data Fusion Using MaximumLikelihood Method and its Application to Underwater Robot

We need to navigate underwater robot to its target. Precision of such navigation in China needs to be upgraded. We upgrade it by using maximum likelihood method and letting the signal processor in the robot fuse the sonar information of both the target and the remote sonar station. We derived eqs.(5), (6) and (10), which are needed for designing the signal processor. Figs.1, 2, and 3 give simulation results for three different cases: (1) target sonar information alone (Fig.1); (2) sonar station information alone (Fig.2); (3) fusion of sonar information of target and sonar station (Fig.3). They show preliminarily but clearly that our data fusion method upgrades navigation precision fairly conspicuously.