带宽受限的集群无人机位姿分布式融合估计器

A Distributed Fusion Estimator with Bandwidth Limitation for Clustered UAVs'Position and Attitude Estimation

为解决集群无人机位姿估计过程中无线通信网络发生的信道拥堵、数据碰撞等网络现象,提出一种带宽受限下的分布式融合估计器。利用传输中介节点部分分量的降维策略,在给定分量选择矩阵和权重矩阵的前提下,建立以滤波增益为决策变量、所有无人机有限时域下状态估计误差协方差阵的迹之和为代价函数的优化方案,并通过最小化代价函数上界获得一组次优的滤波增益,实现了集群无人机位姿递推估计。仿真结果表明,该分布式融合估计能较好地跟踪状态真值;分量选择矩阵和权重矩阵会影响融合估计精度,通过搜索分量选择矩阵的组合,可以获得最优融合估计精度;另外,中介状态估计的权重分布越均匀,融合估计精度越高。

In order to solve such problems as channel congestion and data collision in the wireless communication network during the process of position and attitude estimation of clustered UAVs,a distributed fusion estimator with bandwidth limitation is proposed.With a given component selection matrix and a given weight matrix,and by using the dimension reduction strategy of transporting partial estimated values of intermediate nodes,an optimization scheme is established,which takes filter gains as decision variables and the sum of the trace of the covariance matrix of the state estimation error for all UAVs in the finite time domain as the cost function.Then,a set of sub-optimal filter gain is obtained by minimizing the upper bound of the cost function,and the recursive estimation of position and attitude of the clustered UAVs is realized.Simulation results show that:1) The distributed fusion estimation can track the true value of the state well;2) The component selection matrix and the weight matrix may affect the fusion estimation accuracy,and the optimum fusion estimation accuracy can be obtained by selecting the combination of the component selection matrix;and 3) The more uniform the intermediate state estimation is,the higher the fusion estimation accuracy.