中文摘要：

为了保持未知节点在2个相邻簇之间移动时导航精度的稳定，提出了一种基于H∞滤波的惯性导航系统和无线传感器网络组合导航分布式融合方法．由于组合系统的过程和测量噪声具有未知的但能量有界的统计特性，因此在提出的方法中，用日。滤波器来融合局部估计测量的信息．该滤波器能够根据一定的信息融合准则产生最佳的状态估计．仿真结果显示：与联邦卡尔曼方法相比，提出的方法降低了45％的平均位置误差和85％的平均速度误差．

英文摘要：

In order to keep stable navigation accuracy when the blind node （BN） moves between two adjacent clusters, a distributed fusion method for the integration of the inertial navigation system （INS） and the wireless sensor network （WSN） based on H∞ filtering is proposed. Since the process and measurement noise in the integration system are bounded and their statistical characteristics are unknown, the H∞ filter is used to fuse the information measured from local estimators in the proposed method. Meanwhile, the filter can yield the optimal state estimate according to certain information fusion criteria. Simulation results show that compared with the federal Kalman solution, the proposed method can reduce the mean error of position by about 45% and the mean error of velocity by about 85 %.