无人机集群高斯置信传播协同导航算法  

Gaussian Belief Propagation Based Collaborative Navigation Method for UAV Swarm

作　　者：宋丰毅 熊智[1] 陈明星 王融[1] 马铭江 SONG Fengyi;XIONG Zhi;CHEN Mingxing;WANG Rong;MA Mingjiang(Nanjing University of Aeronautics and Astronautics,Nanjing 211000,China)

机构地区：[1]南京航空航天大学,南京211000

出　　处：《电光与控制》2023年第9期68-73,共6页Electronics Optics & Control

基　　金：国家自然科学基金(61873125,62073163);基础加强计划技术×××领域基金(2021-JCJQ-JJ-0308);上海航天科技创新基金项目(SAST2019-085)。

摘　　要：针对无人机集群的协同导航问题,提出了一种基于高斯置信传播的无人机集群协同导航算法。该算法通过概率图模型对无人机自身传感器信息和无人机机间测距信息进行建模,引入高斯置信传播(GaBP)算法完成协同信息的有效融合。仿真实验结果表明,新算法相较于传统协同扩展卡尔曼滤波导航算法将无卫星信号无人机定位精度从4.82 m提高到了1.97 m。同时,在性能相近的情况下,相较于传统的置信传播算法,新算法的计算效率提升了近40倍。To solve the problem of collaborative navigation of UAV swarm,a method for collaborative navigation of UAV swarm based on Gaussian Belief Propagation(GaBP)is proposed.The sensor information of the UAV itself and the ranging information of the UAV swarm are modeled through the probabilistic graphical model,and the GaBP algorithm is introduced to complete the effective fusion of collaborative information.The simulation results show that,compared with the traditional collaborative Extended Kalman Filter(EKF)navigation method,the new method improves the positioning accuracy of the UAV without satellite signals from 4.82 m to 1.97 m.At the same time,under the condition of similar performance,the computational efficiency of the new algorithm is improved by nearly 40 times compared with that of the traditional belief propagation algorithm.

关 键 词：无人机集群 协同导航 高斯置信传播(GaBP) 概率图模型 

分 类 号：V249.3[航空宇航科学与技术—飞行器设计]