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在基于惯性导航系统和无线传感器网络的组合导航系统中,为了解决传统导航信息松组合方法中测量信息可观性较差的问题,提出了一种基于卡尔曼滤波器的导航信息紧组合模型.当无线传感器网络的信号可用时,组合导航系统将惯性导航系统测量得到的未知节点与已知节点的距离与无线传感器网络测量得到的距离作差,差值作为卡尔曼滤波器的测量信息.由于新测量信息具有更好的可观性和独立性,该方法有效地提高了卡尔曼滤波器的准确度.仿真结果显示,提出的方法平均位置误差比松组合方法降低50%左右,但平均速度误差却略高于松组合方式.
In the integrated navigation system based on inertial navigation system and wireless sensor network, in order to solve the problem of poor observability of measurement information in the traditional navigation information loose combination method, a new navigation information tight combination model based on Kalman filter is proposed. When the wireless sensor network signal is available, the integrated navigation system makes the distance between the unknown node and the known node measured by the inertial navigation system and the distance measured by the wireless sensor network worse, and the difference is used as the measurement information of the Kalman filter. The measurement information has better observability and independence, and the method effectively improves the accuracy of the Kalman filter.The simulation results show that the proposed method reduces average position error by about 50% compared with the loose combination method, but the average velocity error Slightly higher than the loose combination.