期刊文献+

基于修正似然滤波的无人机编队相对导航方法 被引量:2

Relative navigation method based on modified likelihood filtering for unmanned aerial vehicle formation
下载PDF
导出
摘要 针对无人机编队相对导航系统中视觉导航传感器量测数据存在随机时延问题,提出一种能够处理多步随机延迟量测的修正似然容积卡尔曼滤波(ML-CKF)算法。用多个伯努利随机变量对量测模型进行修正以描述随机延迟;通过边缘化延迟变量来计算滤波的似然函数以从延迟量测中提取准确的信息;采用三阶球面-径向容积准则计算高斯加权积分以解决系统的非线性。滤波中的加权因子根据接收量测的特性进行调整,因此,所提修正似然滤波具有自适应卡尔曼滤波属性。利用罗德里格斯参数表示姿态误差,设计了基于修正似然容积卡尔曼滤波的相对导航滤波器。仿真结果表明:所提算法可以准确地估计出长机和僚机之间的相对位置、速度和姿态,且估计精度高于容积卡尔曼滤波和传统随机时延滤波。 A modified likelihood cubature Kalman filtering(ML-CKF)is proposed to solve the problem that the measurements of vision-based relative navigation sensor for unmanned aerial vehicle formation are randomly delayed by multiple steps.The measurement model is modified by the Bernoulli random variables to describe the random delay.The likelihood function of the filtering is calculated by marginalizing out the delay variable to extract accurate information from the delayed measurements.The third-degree spherical-radial rule is utilized to compute the Gaussian-weighted integrals for the nonlinear system.The proposed modified likelihood filtering has the property of adaptive filtering because the weighting factors of the filtering are tuned based on the characteristics of the received measurements.By utilizing the Rodrigues parameters to denote the attitude errors,the relative navigation filter of unmanned aerial vehicle formation is designed based on the ML-CKF.Simulation results indicate that the proposed filtering algorithm could accurately estimate the relative position,velocity and attitude between the leader and follower.Moreover,the estimation accuracy of ML-CKF is superior to cubature Kalman filtering and conventional randomly delayed filtering.
作者 苏炳志 王磊 张红伟 汪海涵 石璐璐 SU Bingzhi;WANG Lei;ZHANG Hongwei;WANG Haihan;SHI Lulu(China Helicopter Research and Development Institute,Tianjin 300300,China;Aviation Military Representation Office of Army Armament Department in Tianjin Region,Tianjin 300384,China)
出处 《北京航空航天大学学报》 EI CAS CSCD 北大核心 2023年第3期569-579,共11页 Journal of Beijing University of Aeronautics and Astronautics
关键词 无人机编队 相对导航 似然函数 容积卡尔曼滤波 随机延迟量测 unmanned aerial vehicle formation relative navigation likelihood function cubature Kalman filtering randomly delayed measurements
  • 相关文献

参考文献6

二级参考文献38

  • 1王建刚,王福豹,段渭军.加权最小二乘估计在无线传感器网络定位中的应用[J].计算机应用研究,2006,23(9):41-43. 被引量:50
  • 2张正勇,孙智,王刚,余荣,梅顺良.基于移动锚节点的无线传感器网络节点定位[J].清华大学学报(自然科学版),2007,47(4):534-537. 被引量:20
  • 3EVA N, WU. A relative navigation system for formation flight [ J ]. IEEE Transaction on Aerospace and Electronic System, 1997,33 (3) : 958 - 967. 被引量:1
  • 4Glenn Bever, Peter Urschel, Curtis Hanson. Comparison of relative navigation solution applied betweenTwo aircraft[R]. AIAA's 1st Technical Conference and Workshop on Unmanned Aerospace Vehicles, AIAA - 2002 - 3440. 被引量:1
  • 5Setmg-Min Oh, Eric N, Johnson. Relative motion estimation for visiva-based formation flight using unscented kahnan filter[R]. AIAA Guidance Navigation and Control Conference, AIAA- 2007- 6866. 被引量:1
  • 6Adam M, Foshnry, John L, Crassidis. Relative navigation of air vehicles[ J]. Journal of Guidance, Control, and Dynamics, 2008,31 (4): 824 - 834. 被引量:1
  • 7Thomas Dall Larson, Nils A, Anderson, Ole Ravn, et al. Incorporation of time delayed measurements in a discrete-time kalman filter[ R]. Proceedings of the 37th IEEE Conference on Decision & Control 1998 : 3972 - 3977. 被引量:1
  • 8PACK D J,DELIMA P, TOUSSAINT G J, et al. Cooperative control of UAVs for localization of intermittently emitting mobile targets [ J ]. IEEE Transactions on Systems, Man, and Cybernet- ics, Part B : Cybernetics ,2009,39 ( 4 ) :959-970. 被引量:1
  • 9ABDELKRIM N,AOUF N, TSOURDOS A, et al. Robust non- linear filtering for INS/GPS UAV localization [ C ] //Proceed- ings of the 16th Mediterranean Conference on Control and Auto- mation. Piscataway, NJ : IEEE Press, 2008 : 695 -702. 被引量:1
  • 10GODHA S,LACHAPELLE G,CANNON M E. Integrated GPS/ INS system for pedestrian navigation in a signal degraded envi- ronment[ C ]//Proceedings of the 19th International Technical Meeting of the Division of the Institute of Navigation ( ION GNSS 2006 ). Fairfax, VA: Institute of Navigation, 2006: 2151-2164. 被引量:1

共引文献31

同被引文献30

引证文献2

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部