Improvement to classical coning algorithms in maneuver performance based on a match correction structure

Abstract

An improved class of coning algorithms is presented to promote the maneuver performance of attitude updating of strapdown inertial navigation system. The improved coning algorithm is based on the match correction structure which can be designed through revising the previous half-compressed correction structure. The improved algorithm coefficient is designed from the existing compressed algorithm according to a given relationship. In order to analyze and evaluate algorithm performance under maneuver environments, two algorithm error models are defined. Compared with the classical compressed coning algorithm, the improved coning algorithm of the corresponding version has the same algorithm throughput and coning accuracy but has higher maneuver accuracy. Especially, the improved four-sample algorithm has about two times of maneuver accuracy compared with its classical compressed version.

Keywords

Coning algorithm match correction structure maneuver accuracy

Get full access to this article

View all access options for this article.

References

Jordan JW. An accurate strapdown direction cosine algorithm. NASA TN : D-5384, 1969.

Bortz

. A new mathematical formulation for strapdown inertial navigation. IEEE Trans Aerosp Electron Syst 1971; AES-7: 61–66.

Miller

. A new strapdown attitude algorithm. J Guid Control Dyn 1983; 6: 287–291.

Ignagni

. Optimal strapdown attitude integration algorithms. J Guid Control Dyn 1990; 13: 363–369.

Lee

Yoon

Mark

et al.

Extension of strapdown attitude algorithm for high-frequency base motion. J Guid Control Dyn 1990; 13: 738–743.

Jiang

Lin

. Improved strapdown coning algorithms. IEEE Trans Aerosp Electron Syst 1992; 28: 484–489.

Ignagni

. Efficient class of optimized coning compensation algorithms. J Guid Control Dyn 1996; 19: 424–429.

Savage

. Coning algorithm design by explicit frequency shaping. J Guid Control Dyn 2010; 33: 1123–1132.

Savage

. Explicit frequency-shaped coning algorithms for pseudo coning environments. J Guid Control Dyn 2011; 34: 774–782.

10.

Mark

Tazartes

. Tuning of coning algorithms to gyro data frequency response characteristics. J Guid Control Dyn 2001; 24: 641–647.

11.

Song

Pan

. Approach to recovering maneuver accuracy in classical coning algorithms. J Guid Control Dyn 2013; 36: 1872–1880.

12.

Tang

Chen

. A class of coning algorithms based on a half-compressed structure. Sensors 2014; 14: 14289–14301.

13.

Zeng

Liu

Xiong

et al.

A high-accuracy attitude algorithm of ring laser gyro strapdown inertial navigation system with pure angle rate output. J Shanghai Jiaotong Univ 2006; 40: 2159–2163. (in Chinese).

14.

Ben

Sun

Gao

et al.

Generalized method for improved coning algorithms using angular rate. IEEE Trans Aerosp Electron Syst 2009; 45: 1565–1572.

15.

Tang

Chen

. A generalized coning correction structure for attitude algorithms. Math Prob Eng 2014; 2014.

16.

Chen

Zhu

et al.

Accuracy analysis of attitude computation based on optimal coning algorithm. Defence Sci J 2012; 62: 361–368.

17.

Tang

Chen

Song

. An approach to improving maneuver performance of coning algorithm. J Southeast Univ (Engl Ed) 2014; 30: 439–444.

18.

Savage

. A unified mathematical framework for strapdown algorithm design. J Guid Control Dyn 2006; 29: 237–249.

19.

Shen

Song

et al.

Temperature drift modeling of MEMS gyroscope based on genetic-Elman neural network. Mech Syst Signal Process 2016; 72–73: 897–905.

20.

Shen

Zhang

et al.

A noise reduction method for dual-mass micro-electromechanical gyroscopes based on sample entropy empirical mode decomposition and time-frequency peak filtering. Sensors 2016; 16: 796–796.