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对等结构下多节点INS误差修正

Multi-node INS error correction based on peer-to-peer structure
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摘要 传统的多目标跟踪系统一般采用集中式与分布式结构,文中在抗毁性差的集中式与分布式结构的基础上提出无中心化的对等式结构模型,针对INS系统误差随时间增长不断累积的问题,提出在对等式结构下修正多节点INS误差的算法。在对等式结构中选择导航精度最高的节点建立非线性运动模型,利用CKF滤波对该节点导航信息进行优化,其余节点利用对等结构可通信合作的优势解算滤波相对距离,与通过各自INS解算出相对位置信息之差作为量测值,建立INS误差修正模型,对INS误差参数进行卡尔曼滤波开环输出校正得到最优INS误差估计值,对各节点INS误差进行补偿。仿真结果表明,CKF滤波对非线性运动模型具有较好的跟踪能力,此算法能够对INS系统误差进行有效修正,具有较高的实时性与可靠性。 Usually,the centralized and distributed structure is adopted in the traditional multi-objective tracking system.On the basis of the centralized and distributed structures with poor invulnerability,a decentralized peer-to-peer structure model is proposed. Since the INS(inertial navigation system)error is accumulated with time expansion,an algorithm based on the peerto-peer structure is proposed for correcting multi-node INS error. The node with the highest navigation accuracy is selected in the peer-to-peer structure to establish a nonlinear motion model. The CKF(cubature Kalman filtering) is used to optimize the navigation information of this node,while the rest of the nodes are used to solve the filtering relative distance by virtue of the advantage that the peer-to-peer structure can perform communication and cooperation. The difference between the filtering relative distance and the relative position information calculated by the respective INS is taken as a measured value to establish an INS error correction model. The open-loop output correction with Kalman filtering is carried out for the INS error parameters to obtain the optimal INS error estimation value,so as to compensate the INS error of each node. The simulation results show that the CKF has a good tracking ability for nonlinear motion model,and can effectively correct the INS error. Therefore,it has high real-time performance and reliability.
作者 李寅龙 张天舒 刘傲 LI Yinlong;ZHANG Tianshu;LIU Ao(Naval Aviation University,Yantai 264001,China)
机构地区 海军航空大学
出处 《现代电子技术》 2021年第17期1-5,共5页 Modern Electronics Technique
基金 国防科技卓越青年人才基金(2017-JCJQ-ZQ-003) 泰山学者工程专项经费资助课题(ts201712072)。
关键词 INS误差修正 对等式结构 运动模型 信息优化 目标跟踪 误差补偿 CKF滤波 INS error correction peer-to-peer structure motion model information optimization target tracking error compensation CKF
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