Applying of Switch Strong Tracking UKF in Spacecraft Autonomous Celestial Navigation
Jingjing Li1, Huayi Li2 and Yingchun Zhang2
(1. Shandong Aerospace Electro-Technology Institute, Yantai 264003, China;2. Research Center of Satellite Technology, Harbin Institute of Technology, Harbin 150001, China)
Abstract:
Star & Horizon sensor based autonomous navigation methods play an increasingly important role in spacecraft celestial navigation. However, the measurements of star sensors and horizon sensor are frequently affected by uncertain noises from space environment. To improve the estimation precision, a state estimation algorithm named Switch Strong Tracking Unscented Kalman Filter(SSTUKF) is presented. Firstly, the adaptive fading factor is deduced through the adoption of unknown instrumental diagonal matrixes to real time rectify the measurement covariance matrix. Secondly, according to the deduction of Chebyshev law of large numbers, innovation criterion is introduced during estimation to decrease the unnecessary calculation. Finally, SSTUKF is suggested through the adoption of adaptive fading factor and innovation criterion. The filter can switch between the normal filter mode and adaptive filter mode. As the calculation of innovation criterion is less than the adaptive fading factor, SSTUKF improves the estimation efficiency. To demonstrate the effectiveness, SSTUKF is applied to Star & Horizon sensor based autonomous navigation system with uncertain measurement noises. The simulation results verify the proposed algorithm.
Key words: autonomous navigation adaptive filter unscented transformation uncertain noise
DOI:10.11916/j.issn.1005-9113.2015.01.013
Clc Number:V448.22+4
Fund:
删除或更新信息,请邮件至freekaoyan#163.com(#换成@)
Applying of Switch Strong Tracking UKF in Spacecraft Autonomous Celestial Navigation
本站小编 哈尔滨工业大学/2019-10-23
相关话题/Applying Switch Strong Tracking UKF
采用UKF算法估计路面附着系数
采用UKF算法估计路面附着系数林棻,黄超(南京航空航天大学车辆工程系,210016南京)摘要:为了能够迅速准确获取当前道路信息以提高汽车主动安全性能,提出一种实时跟踪路面附着系数变化的汽车状态估计方法.建立包含Pacejka89轮胎模型的七自由度非线性汽车动力学模型,通过动力学模型估算出前后车轮 ...哈尔滨工业大学科研学术 本站小编 哈尔滨工业大学 2019-10-24一种结合UKF的疲劳结构剩余寿命预测方法
一种结合UKF的疲劳结构剩余寿命预测方法罗斌,林琳,钟诗胜(哈尔滨工业大学机电工程学院,哈尔滨150001)摘要:针对机械系统中疲劳结构的剩余寿命(RUL)预测问题,提出了一种结合无迹卡尔曼滤波算法(UKF)的RUL预测方法.该方法包括疲劳裂纹性能参数评估和RUL预测两个部分.在性能参数评估部分,通 ...哈尔滨工业大学科研学术 本站小编 哈尔滨工业大学 2019-10-24INS/GPS紧耦合系统中的模糊自应SRUKF算法
INS/GPS紧耦合系统中的模糊自应SRUKF算法袁建国,袁艳涛,刘飞龙,庞宇,林金朝(重庆邮电大学光纤通信技术重点实验室,400065重庆)摘要:为解决惯性导航系统(INS)与全球定位系统(GPS)紧耦合中标准无迹卡尔曼滤波(UKF)由于计算舍入误差使协方差矩阵负定和实际应用中由于量测噪声时变而严 ...哈尔滨工业大学科研学术 本站小编 哈尔滨工业大学 2019-10-24低轨卫星紧组合导航UKF方法
低轨卫星紧组合导航UKF方法姬晓琴,高晓颖北京航天自动控制研究所宇航智能控制技术国家级重点实验室,100854北京摘要:针对紧组合导航系统状态方程及量测方程的非线性,以低轨卫星为应用对象开展了无迹卡尔曼滤波UKF方法研究.给出了惯性系下的系统模型及算法模型,其中姿态直接采用修正Rodrigues参数 ...哈尔滨工业大学科研学术 本站小编 哈尔滨工业大学 2019-10-24Output Feedback Controller Design for Discrete-time Switched Singular Systems
Output Feedback Controller Design for Discrete-time Switched Singular Systems Mao Wang,Yan-Ling Wei, Jia Shi (Space Control and Inertial Technology Research Center, Harbin Institute of Technology,Harbin 150080, China) ...哈尔滨工业大学科研学术 本站小编 哈尔滨工业大学 2019-10-24Adaptive fuzzy tracking control for a class of switched MIMO nonlinear systems
Adaptive fuzzy tracking control for a class of switched MIMO nonlinear systems WANG Yu-fei, JIANG Chang-sheng, WU Qing-xian, ZHANG Qiang College of Automation engineering,Nanjing University of Aeronautics and Astronautics,Nanjin ...哈尔滨工业大学科研学术 本站小编 哈尔滨工业大学 2019-10-24Model Reference Adaptive Control for Switched Systems with Closed-loop Reference Model Under Arbitra
Model Reference Adaptive Control for Switched Systems with Closed-loop Reference Model Under Arbitrary Switching Hao Yang,Jing Xie,Jun Zhao (State Key Laboratory of Synthetical Automation for Process Industries, College of Infor ...哈尔滨工业大学科研学术 本站小编 哈尔滨工业大学 2019-10-23Tracking Algorithm Based on Improved Interacting Multiple Model Particle Filter
Tracking Algorithm Based on Improved Interacting Multiple Model Particle Filter Hailin Feng,Juanli Guo (School of Mathematics and Statistics, Xidian University, Xi’an 710126, China) Abstract: ...哈尔滨工业大学科研学术 本站小编 哈尔滨工业大学 2019-10-23A Novel Tracking-by-Detection Method with Local Binary Pattern and Kalman Filter
A Novel Tracking-by-Detection Method with Local Binary Pattern and Kalman Filter Zhongli Wang1, Chunxiao Jia1, Baigen Cai1, Litong Fan1, Chuanqi Tao2, Zhiyi Zhang2, Yinling Wang2, Min Zhang2and Guoyan Lyu2 (1.School of Electron ...哈尔滨工业大学科研学术 本站小编 哈尔滨工业大学 2019-10-23Non-stationary Buffeting Response Analysis of Long Span Suspension Bridge Under Strong Wind Loading
Non-stationary Buffeting Response Analysis of Long Span Suspension Bridge Under Strong Wind Loading Wenfeng Huang1,2,Kongqing Zou1 (1.School of Civil Engineering, Hefei University of Technology, Hefei 230009, China;2.Department ...哈尔滨工业大学科研学术 本站小编 哈尔滨工业大学 2019-10-23