Journal of Marine Science and Application

, Volume 16, Issue 3, pp 344–351 | Cite as

A comprehensive method for evaluating precision of transfer alignment on a moving base

  • Hongliang Yin (尹洪亮)
  • Bo Xu (徐博)
  • Dezheng Liu (刘德政)


In this study, we propose the use of the Degree of Alignment (DOA) in engineering applications for evaluating the precision of and identifying the transfer alignment on a moving base. First, we derive the statistical formula on the basis of estimations. Next, we design a scheme for evaluating the transfer alignment on a moving base, for which the attitude error cannot be directly measured. Then, we build a mathematic estimation model and discuss Fixed Point Smoothing (FPS), Returns to Scale (RTS), Inverted Sequence Recursive Estimation (ISRE), and Kalman filter estimation methods, which can be used when evaluating alignment accuracy. Our theoretical calculations and simulated analyses show that the DOA reflects not only the alignment time and accuracy but also differences in the maneuver schemes, and is suitable for use as an integrated evaluation index. Furthermore, all four of these algorithms can be used to identify the transfer alignment and evaluate its accuracy. We recommend RTS in particular for engineering applications. Generalized DOAs should be calculated according to the tactical requirements.


transfer alignment precision assessment degree of alignment Kalman smoothing returns to scale moving base engineering applications comprehensive method 



Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Allan DW, 1987. Time and frequency (time-domain) characterization, estimation, and prediction of precision clocks and oscillators. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 34(6), 647–654 DOI: 10.1109/T-UFFC.1987.26997CrossRefGoogle Scholar
  2. Andrews A, 1968. A square root formulation of the Kalman covariance equations. AIAA Journal, 6(6), 1165–1166. DOI: 10.2514/3.4696CrossRefMATHGoogle Scholar
  3. Chen JJ, Han XM, Nan HY, 2014. Integrated evaluation of developing plan of air and missile defense warhead by grey clustering theory. Journal of Air Force Engineering University (Natural Science Edition), 1(3), 29–33. DOI: 10.3969/j.issn.1009-3516.2014.01.007Google Scholar
  4. Cheng GX, Zhang SF, 2001. Assessment for the accuracy of the fall points -probability circle method. Journal of National University of Defense Technology, 10(2): 332–338. DOI: 10.3969/j.issn.1001-2486.2001.05.004Google Scholar
  5. Crassidis JL, 2006. Sigma-point Kalman filtering for integrated GPS and inertial navigation, IEEE Transactions on Aerospace and Electronic Systems, 42(2), 750–756. DOI: 10.1109/TAES.2006.1642588Google Scholar
  6. Gao Y, Sun W, Xu AG, 2012. Fiber optic gyroscope for application at attitude determination systems. Aerospace & Electronic Systems Magazine IEEE, 27(4), 32–38. DOI: 10.1109/MAES.2012.6203716Google Scholar
  7. Grewal MS, Weill LR, Andrews AP, 2007, Global positioning systems, inertial navigation and integration. John Willey & Sons. New York, United States, 380–382 DOI: 10.1002/0470099720CrossRefGoogle Scholar
  8. Han PX, Cui NG, Mu RJ, 2010. Comparison between transfer alignments of inertial navigation system in two coordinates. Journal of Chinese Inertial Technology, 18(3): 272–278. DOI: 10.13695/j.cnki.12-1222/o3.2010.03.015Google Scholar
  9. Hinneburg A, Mannila H, Kaislaniemi S, 2006. How to handle small samples: Bootstrap and Bayesian methods in the analysis of linguistic change. Literary & Linguistic Computing, 6(1), 62–70. DOI: 10.1093/llc/fqm006Google Scholar
  10. Leng S, Wang JH, Wang LX, Zhang Q, 2012. Fall point dispersion of strapdown missile intensive test based on the integrated sequential truncation method. Science Technology and Engineering, 12(28), 7480–7484 DOI: 10.3969/j.issn.1671-1815.2012.28.071Google Scholar
  11. Miao LJ, Tian H, 2000. Fast initial alignment and its errors of RLG strapdown inertial navigation system for land vehicle. Journal of Beijing Institute of Technology, 20(2), 205–209 DOI: 10.15918/j.tbi t1001 -0645.2000.02.016Google Scholar
  12. Przemyslaw B, 2012. Enhancing positioning accuracy in urban terrain by fusing data from a GPS receiver, inertial sensors, stereo-camera and digital maps for pedestrian navigation. Sensors, 12(6), 6764–6801. DOI: 10.3390/s120606764Google Scholar
  13. Rogers R, 1991. Velocity-plus-rate matching for improved tactical weapon rapid transfer alignment, Navigation and Control Conference, New Orleans, United States, 1580–1588 DOI: 10.2514/6.1991-2783Google Scholar
  14. Rogers RM, 1996. Weapon IMU transfer alignment using aircraft position from actual flight tests. IEEE 1996: Position Location and Navigation Symposium. Atlanta, United States. 328–335. DOI: 10.1109/PLANS.1996.509096Google Scholar
  15. Wang YY, Yang GL, 2012. Comprehensive assessment of methods for calculating circular error probability of inertial positioning. International Conference on Electronics. Harbin, China, 2190–2194. DOI: 10.1109/ICECC.2012.400Google Scholar
  16. Wang HS, YU DY, 2014. Multilayer interception method of ballistic missile and effectiveness evaluation. Journal of Sichuan Ordnance, 15(3), 25–31. DOI: 10.11809/scbgxb2014.06.007Google Scholar
  17. WANG YY, YANG GL, 2013. Comprehensive assessment for dynamic transfer alignment accuracy of strap-down inertial navigation system. Journal of Chinese Inertial Technology, 21(4), 425–429 DOI: 10.13695/j.cnki.12-1222/o3.2013.04.011MathSciNetGoogle Scholar
  18. Zhang SF, Yang HB, Cai Hong, 2008. Inertial guidance weapon precision analysis and evaluation. Defense Technological University Press, Changsha, China, 20–25Google Scholar
  19. Zhang SF, 2002. A method for the detection of precision of random fall points. Acta Armamentarii, 6(1): 63–70. DOI: 10.3321/j.issn:1000-1093.2002.02.028MathSciNetGoogle Scholar
  20. Zheng XB, Dong JX, Zhang ZG, 2011. Monte Carlo evaluation for fall point dispersion of ballistic missile based on prior information. Journal of Chinese Inertial Technology, 19(1), 116–121 DOI: 10.13695/j.cnki.12-1222/03.2011.01.021Google Scholar

Copyright information

© Harbin Engineering University and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Hongliang Yin (尹洪亮)
    • 1
    • 2
  • Bo Xu (徐博)
    • 3
  • Dezheng Liu (刘德政)
    • 3
  1. 1.China Ship Research and Development AcademyBeijingChina
  2. 2.Department of Precision InstrumentTsinghua UniversityBeijingChina
  3. 3.School of AutomationHarbin Engineering UniversityHarbinChina

Personalised recommendations