基于记忆融合模式的多无人机分散式协同导航方法

Multi-UAV decentralized cooperative navigation method based on memory-fusion

针对多无人机协同交互过程中存在的通信时滞问题,提出基于记忆-融合的多无人机分散式协同导航算法。在无人机惯性和全球卫星导航系统(GNSS)紧组合导航框架基础上,建立含时滞影响的系统状态向量,并对系统状态误差及其方差进行推导,进一步构建关于各无人机状态的最优估计模型,并基于状态误差方差最小准则对状态进行最优估计。建立了基于机间相对测量的多无人机分散式协同导航算法,提出了基于记忆融合模式的时滞处理方法。在GNSS可获取及拒止环境下进行多无人机协同导航仿真与实验测试,结果表明,所提出的基于记忆-融合的分散式协同导航算法能有效补偿通信时滞造成的精度损失,有效提高定位精度。

To address the communication delay problem during cooperative interaction of multiple Unmanned Aerial Vehicles(UAVs),a memory-fusion based multi-UAV decentralized cooperative navigation algorithm is proposed.On the basis of the UAV inertial and Global Navigation Satellite System(GNSS)tightly combined navigation framework,the system state vector considering the effect of communication delay is established,and the system state error and its variance are derived.Then the optimal estimation model about the state of each UAV is constructed.,and the optimal state is estimated based on the criterion of minimum variance of the state error.A decentralized cooperative navigation algorithm for multiple UAVs is established based on inter-aircraft relative measurements,and a time delay processing method is proposed based on the memory fusion model.The results show that the proposed algorithm can effectively compensate for the loss of accuracy caused by communication delay and improve the positioning accuracy.