AEROSPACE CHINA

中国航天科技集团有限公司主管

中国航天系统科学与工程研究院主办

ISSN 1671-0940

CN 11-4673/V

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AEROSPACE CHINA ›› 2019, Vol. 20 ›› Issue (1): 3-8.doi: 10.3969/j.issn.1671-0940.2019.01.001

• 学术研究 •    下一篇

Application of Genetic Algorithm in Estimation of Gyro Drift Error Model

  

  • 出版日期:2019-03-19 发布日期:2019-04-14

Application of Genetic Algorithm in Estimation of Gyro Drift Error Model

LI Dongmei, BAI Taixun, HE Xiaoxia*, ZHANG Rong Department of Precision Instrument, Tsinghua University, Beijing 100084#br#   

  • Online:2019-03-19 Published:2019-04-14
  • Contact: HE Xiaoxia, Ph.D, Department of Precision Instrument, Tsinghua University.
  • About author:LI Dongmei (1973- ) received her Ph.D degree from the Harbin Institute of Technology. She is an associate professor in the Department of Precision Instrument of Tsinghua University and is engaged in inertial sensor and inertial navigation system, precision control system and digital signal processing.

Abstract: Extended Kalman Filter (EKF) algorithm is widely used in parameter estimation for nonlinear systems. The estimation precision is sensitively dependent on EKF’s initial state covariance matrix and state noise matrix. The grid optimization method is always used to find proper initial matrix for off-line estimation. However, the grid method has the draw back being time consuming hence, coarse grid followed by a fine grid method is adopted. To further improve efficiency without the loss of estimation accuracy, we propose a genetic algorithm for the coarse grid optimization in this paper. It is recognized that the crossover rate and mutation rate are the main influencing factors for the performance of the genetic algorithm, so sensitivity experiments for these two factors are carried out and a set of genetic algorithm parameters with good adaptability were selected by testing with several gyros’ experimental data. Experimental results show that the proposed algorithm has higher efficiency and better estimation accuracy than the traversing grid algorithm.