SINS/ANS integration for augmented performance navigation solution using unscented Kalman filtering

被引:24
|
作者
Ali, J [1 ]
Fang, JC [1 ]
机构
[1] Beijing Univ Aeronaut & Astronaut, Sch Instrumentat Sci & Optoelect Engn, Beijing 100083, Peoples R China
关键词
integrated navigation; SINS; astronavigation; unscented Kalman filter;
D O I
10.1016/j.ast.2005.11.009
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The fundamental concept of the multisensor integrated navigation system is the utilization of a medium precision INS in conjunction with one or more auxiliary sensors which perform as error bounding sources. Strapdown inertial navigation system (SINS) integrated with astronavigation system (ANS) yields reliable mission capability and enhanced navigational accuracy for spacecrafts. The theory and characteristics of integrated system based on unscented Kalman filtering is investigated in this paper. This Kalman filter structure uses unscented transform to approximate the result of applying a specified nonlinear transformation to a given mean and covariance estimate. The filter implementation subsumed here is in a direct feedback mode. Axes misalignment angles of the SINS are observation to the filter. A simple approach for simulation of axes misalignments using stars observation is presented. The SINS error model required for the filtering algorithm is derived in space-stabilized mechanization. Simulation results of the integrated navigation system using a medium accuracy SINS demonstrates the validity of this method on improving the navigation system accuracy with the estimation and compensation for gyros drift, and the position and velocity errors that occur due to the axes misalignments. (C) 2005 Elsevier SAS. All rights reserved.
引用
收藏
页码:233 / 238
页数:6
相关论文
共 50 条
  • [31] Performance enhancement of PPP/SINS tightly coupled navigation based on improved robust maximum correntropy kalman filtering
    Zhang, Laihong
    Lou, Yidong
    Song, Weiwei
    Zhang, Weixing
    Peng, Zhuang
    ADVANCES IN SPACE RESEARCH, 2024, 74 (05) : 2078 - 2091
  • [32] Unscented Kalman Filtering for Ultra-tightly Coupled GPS/INS Integration
    Yuan, Gannan
    Zhang, Tao
    2009 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS 1-7, CONFERENCE PROCEEDINGS, 2009, : 4556 - 4560
  • [33] Sensorless vector control of an IPMSM using Unscented Kalman Filtering
    Ndjana, H. J. Nanga
    Lautier, Ph.
    2006 IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS, VOLS 1-7, 2006, : 2242 - +
  • [34] SINS/GPS tightly integrated navigation system based on quaternion square root unscented Kalman filter
    Zhou W.-D.
    Qiao X.-W.
    Ji Y.-R.
    Hao Y.-L.
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2010, 32 (12): : 2643 - 2647
  • [35] FILTERING METEOROID FLIGHTS USING MULTIPLE UNSCENTED KALMAN FILTERS
    Sansom, E. K.
    Bland, P. A.
    Rutten, M. G.
    Paxman, J.
    Towner, M. C.
    ASTRONOMICAL JOURNAL, 2016, 152 (05):
  • [36] An Adaptive Unscented Kalman Filtering Approach using Selective Scaling
    Kim, Jaehoon
    Kiss, Balint
    Lee, Dongik
    2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2016, : 784 - 789
  • [37] Disturbance Estimation and Wave Filtering Using an Unscented Kalman Filter
    Wirtensohn, Stefan
    Schuster, Michael
    Reuter, Johannes
    IFAC PAPERSONLINE, 2016, 49 (23): : 518 - 523
  • [38] Unscented Kalman Filtering for Attitude Determination Using MEMS Sensors
    Shiau, Jaw-Kuen
    Wang, I-Chiang
    JOURNAL OF APPLIED SCIENCE AND ENGINEERING, 2013, 16 (02): : 165 - 176
  • [39] Unscented Kalman Filtering for Localization using Range or Bearing Data
    O'Brien, Richard T., Jr.
    Kutzer, Michael D. M.
    2024 UKACC 14TH INTERNATIONAL CONFERENCE ON CONTROL, CONTROL, 2024, : 262 - 267
  • [40] Improved Cubature Kalman Filtering for Tightly Coupled GPS/SINS Integrated Navigation System
    Zhu Wei
    Wang Wei
    Yuan Gannan
    2016 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, 2016, : 983 - 987