GNSS/INS/VNS组合定位信息融合的多无人机协同导航方法  

Multi-UAV Cooperative Navigation Method Based on Fusion of GNSS/INS/VNS Positioning Information

作　　者：曹正阳 张冰 白屹轩 勾柯楠 CAO Zhengyang;ZHANG Bing;BAI Yixuan;GOU Kenan(Xi'an ASN UAV Technology Co.,Ltd.,Xi'an 710065,Shaanxi,China;State Key Laboratory for Strength and Vibration of Mechanical Structures,Xi'an Jiaotong University,Xi'an 710049,Shaanxi,China;College of Information Science and Engineering,Northeastern University,Qinhuangdao 066099,Hebei,China)

机构地区：[1]西安爱生无人机技术有限公司,陕西西安710065 [2]西安交通大学复杂服役环境重大装备结构强度与寿命全国重点实验室,陕西西安710049 [3]东北大学信息科学与工程学院,河北秦皇岛066099

出　　处：《兵工学报》2023年第S02期157-166,共10页Acta Armamentarii

基　　金：陕西省重点研发计划项目(2022ZDLGY03-01)。

摘　　要：在信息化战场上,无人机面临多种潜在威胁,不时出现的非意图干扰对无人机系统的卫星信号和通信链路造成干扰,对飞行产生不良影响。为了解决这一挑战,采用多传感器信息融合,以全球导航卫星系统(Global Navigation Satellite System,GNSS)和惯性导航系统(Inertial Navigation System,INS)组合导航系统为主滤波器,并将全球定位系统导航系统和视觉导航系统作为子滤波器,建立了联合滤波器。将多架无人机数字影像的相对导航信息与各无人机平台获取的绝对导航信息融合,实现了一种基于卡尔曼滤波的多地标接力辅助导航算法,有效提高了GNSS/INS相对导航系统的解算精度,降低了多无人机群体的计算负担,扩大了无人机的巡航范围。采用并行分布式的系统框架,将算法部署在多个无人机平台上,通过无人机之间的信息传递和互动,实现多无人机的协同感知与自主定位。在仿真任务场景中进行相关实验,实验结果显示该方法在3架无人机协同导航中位置估计平均误差达到0.66 m,速度估计精度保持在±0.4 m/s,满足设计要求。In the informationized battlefield,the unmanned aerial vehicles(UAVs)face various potential threats,including intermittent unintentional interference that disrupts the satellite signals and communication links of unmanned aircraft systems(UAS),leading to adverse effects on flight.To address this challenge,the multi-sensor data is utilized,and a joint filter is established usingthe global navigation satellite system(GNSS)and inertial navigation system(INS)combination navigation system as the main filter,and the global positioning system(GPS)and visual navigation system(VNS)as sub-filters.This approach fuses the relative navigation information from multiple UAVs digital image maps with the absolute navigation information acquired by each UAV platform,creating a Kalman filter-based multi-landmark relay-assisted navigation algorithm.This effectively enhances the solution accuracy of GNSS/INS relative navigation systems,reduces the computational burden on multi-UAVs,and expands the cruising range of UAVs.Additionally,a parallel distributed system framework is used to deploy the algorithm on multiple UAV platforms and facilitatethe information sharing and interaction among UAVs,thereby achieving the collaborative perception and autonomous positioning of multi-UAVs.The experiments conducted in simulated mission scenarios demonstrate that this approach meets the precision requirements,achieving an average positional estimation error of 0.66 mand maintaining the velocity estimation accuracy within±0.4 m/s in the collaborative navigation of three UAVs.

关 键 词：无人机 协同导航 卡尔曼滤波算法 GNSS/INS组合 视觉导航 

分 类 号：V249.3[航空宇航科学与技术—飞行器设计] TN967.2[电子电信—信号与信息处理]