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 Hongliang Yin,Bo Xu,Dezheng Liu.A Comprehensive Method for Evaluating Precision of Transfer Alignment on a Moving Base[J].Journal of Marine Science and Application,2017,(3):344-351.[doi:10.1007/s11804-017-1416-8]
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A Comprehensive Method for Evaluating Precision of Transfer Alignment on a Moving Base
Hongliang Yin12 Bo Xu3 Dezheng Liu3
Hongliang Yin12 Bo Xu3 Dezheng Liu3
1. China Ship Research and Development Academy, Beijing 100192, China;
2. Department of Precision Instrument, Tsinghua University, Beijing 100084, China
transfer alignmentprecision assessmentdegree of alignmentKalman smoothingreturns to scalemoving baseengineering applicationscomprehensive method
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.


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
Andrews A, 1968. A square root formulation of the Kalman covariance equations. AIAA Journal, 6(6), 1165-1166.
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.
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.
Crassidis JL, 2006. Sigma-point Kalman filtering for integrated GPS and inertial navigation, IEEE Transactions on Aerospace and Electronic Systems, 42(2), 750-756.
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.
Grewal MS, Weill LR, Andrews AP, 2007, Global positioning systems, inertial navigation and integration. John Willey & Sons. New York, United States, 380-382
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.
Hinneburg A, MannilaH, 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.
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
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. 016
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.
Rogers R, 1991. Velocity-plus-rate matching for improved tactical weapon rapid transfer alignment, Navigation and Control Conference, New Orleans, United States, 1580-1588
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.
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.
Wang HS,YU DY, 2014. Multilayer interception method of ballistic missile and effectiveness evaluation. Journal of Sichuan Ordnance, 15(3), 25-31.
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
Zhang SF, Yang HB, Cai Hong, 2008. Inertial guidance weapon precision analysis and evaluation. Defense Technological University Press, Changsha, China, 20-25
Zhang SF, 2002. A method for the detection of precision of random fall points. Acta Armamentarii, 6(1):63-70.
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


Received date: 2016-07-30;Accepted date:2017-03-10。
Foundation item:Supported by the National Natural Science Foundation of China (61633008), the National Natural Science Foundation of China (61203225), the Natural Science Foundation of Heilongjiang Province of China(QC2014C069), the Special fund for the Central Universities (HEUCF160401), and Provincial Postdoctoral Scientific Research Foundation (LBH-Q15032).
Corresponding author:Bo Xu,xubocartor@sina.com
Last Update: 2017-08-31