Backtracking Velocity Denoising Based Autonomous In-Motion Initial Alignment

被引:9
作者
Li, Feng [1 ]
Xu, Jiangning [1 ]
He, Hongyang [1 ]
机构
[1] PLA Naval Univ Engn, Dept Nav Engn, Wuhan 430033, Hubei, Peoples R China
来源
IEEE ACCESS | 2018年 / 6卷
基金
美国国家科学基金会;
关键词
Strapdown inertial navigation system; initial alignment; autonomous; ATTITUDE; INTEGRATION; SCHEME;
D O I
10.1109/ACCESS.2018.2877624
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the global navigation satellite system denial environment, strap-down inertial navigation system (SINS) has to rely on the body-frame velocity output by autonomous velocity measurement equipment, such as odometer and Doppler velocity log, to implement the in-motion initial alignment. Considering the external velocity noise and the approximation existing in the body-frame velocity aided initial alignment model, the autonomous in-motion alignment for SINS with high precision is a difficult problem. Besides, the position updating of SINS cannot be realized only depending on the body-frame velocity. The position error will negatively impact the precision of the following fine alignment and navigation. In this paper, a backtracking velocity denoising-based autonomous in-motion initial alignment is proposed. Forward compass alignment and backward compass alignment are carried out, respectively, to denoise the external velocity. Body-frame velocity-based and navigation-frame velocity-based attitude determination are implemented, respectively, to gradually realize the attitude alignment. The contributions of the work presented here are twofold. First, vehicle velocity during the whole initial alignment process is accurately denoised and determined based on the backtracking compass alignment. Second, high precision position alignment is achieved during the attitude determination. The validity of the proposed method is verified based on field test data.
引用
收藏
页码:67144 / 67155
页数:12
相关论文
共 23 条
  • [1] Chang L., 2014, OPTIMIZATION BASED A
  • [2] Backtracking Integration for Fast Attitude Determination-Based Initial Alignment
    Chang, Lubin
    Hu, Baiqing
    Li, Yang
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2015, 64 (03) : 795 - 803
  • [3] Initial Alignment by Attitude Estimation for Strapdown Inertial Navigation Systems
    Chang, Lubin
    Li, Jingshu
    Chen, Shengyong
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2015, 64 (03) : 784 - 794
  • [4] A Novel Backtracking Scheme for Attitude Determination-Based Initial Alignment
    Chang, Lubin
    Qin, Fangjun
    Li, An
    [J]. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2015, 12 (01) : 384 - 390
  • [5] Dongqing Gu, 2008, 2008 IEEE/ION Position, Location and Navigation Symposium - PLANS 2008, P961, DOI 10.1109/PLANS.2008.4570038
  • [6] Study on Innovation Adaptive EKF for In-Flight Alignment of Airborne POS
    Fang Jiancheng
    Yang Sheng
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2011, 60 (04) : 1378 - 1388
  • [7] A Self-Calibration Method for Non-Orthogonal Angles of Gimbals in Tri-Axis Rotational Inertial Navigation System
    Gao, Pengyu
    Li, Kui
    Wang, Lei
    Gao, Jiaxin
    [J]. IEEE SENSORS JOURNAL, 2016, 16 (24) : 8998 - 9005
  • [8] Groves PD, 2008, ARTECH HSE GNSS TECH, P3
  • [9] Genetic algorithm based optimal compass alignment
    He, Hongyang
    Xu Jiangning
    Feng, Li
    Miao, Wu
    [J]. IET RADAR SONAR AND NAVIGATION, 2016, 10 (02) : 411 - 416
  • [10] Hongyang H., 2015, P I MECH ENG G-J AER, V230, P1518