一种面向多无人机协同感知的分布式融合估计方法

Distributed fusion estimation algorithm for multi-UAVs cooperative sensing

针对基于扩展卡尔曼滤波的融合估计算法存在线性化误差,且分布式融合计算复杂等问题,基于无色变换、交互多模型和信息滤波,采用递阶分布式融合估计结构,提出一种分布式无色信息滤波算法.该方法中的无色变换能够保证更高的估计精度,交互多模型使其具有更好的鲁棒性,信息形式的卡尔曼滤波使融合估计计算变得简单.仿真结果表明,该算法能够提高多无人机融合估计性能.

To the problem of fusion estimation for coordinated unmanned aerial vehicles（UAVs）,a method is presented.Based on unscented Kalman filter,distributed information filter and interacting multiple model,within a hierarchically distributed fusion architecture,an algorithm named interacting multiple model-distributed unscented information filter（IMMDUIF） is suggested,which takes important properties for estimating accuracy（unscented transform）,robustness（interacting multiple model）,and fusion ability（information）.Simulation results show that the proposed method can significantly improve the fusion estimation performance of the multi-UAVs.