系统仿真学报 ›› 2019, Vol. 31 ›› Issue (11): 2485-2491.doi: 10.16182/j.issn1004731x.joss.19-FZ0338

• 仿真应用工程 • 上一篇    下一篇

基于减空间搜索算法的IMU动态系数标定设计

闫宏雁, 张宇, 朱伟华, 史明, 张业鑫   

  1. 上海机电工程研究所,上海 201100
  • 收稿日期:2019-05-29 修回日期:2019-07-18 出版日期:2019-11-10 发布日期:2019-12-13
  • 作者简介:闫宏雁(1992-),男,黑龙江,硕士生,研究方向为仿真控制;张宇(1985-),男,黑龙江,硕士生,高工,研究方向为仿真控制;朱伟华(1972-),男,上海,本科生,研究员,研究方向为仿真控制。

Design of IMU Dynamic Coefficient Calibration Based on Reduced Space Search Algorithm

Yan Hongyan, Zhang Yu, Zhu Weihua, Shi Ming, Zhang Yexin   

  1. Shanghai Institute of Mechanical and Electrical Engineering, Shanghai 201100, China
  • Received:2019-05-29 Revised:2019-07-18 Online:2019-11-10 Published:2019-12-13

摘要: 为提高标定捷联惯组动态误差系数的速度,提出在惯性导航系统中建立动力学误差模型,利用卡尔曼滤波反映误差项的观测度,确定最优算法的目标函数。针对减空间搜索算法的罚函数采用遗传算法进行分析改进,在末端时,既摆脱了局部伪最优解对结果的干扰,又在接近最优解时提高辨识速度。与共轭梯度法的求解时长进行比较,验证了改进减空间搜索算法对动态系数标识的高效性,有效解决捷联惯组动态误差无法快速补偿的问题。

关键词: 捷联式惯性导航系统, 共轭梯度算法, 减空间搜索法, 动态误差标定

Abstract: In order to improve the dynamic error coefficient speed of the calibration strapdown inertial group, a dynamic error model is established in the inertial navigation system. The Kalman filter is used to reflect the observation degree of the error term to determine the objective function of the optimal algorithm. The penalty function for the reduced space search algorithm is improved by genetic algorithm. At the end, it not only gets rid of the interference of the local pseudo-optimal solution, but also improves the recognition speed when it is close to the optimal solution. Compared with the solution length of the conjugate gradient method, the efficiency of the improved reduced space search algorithm for dynamic coefficient identification is verified, and the problem that the dynamic error of the strapdown inertial group cannot be quickly compensated is effectively solved.

Key words: stapdown inertial navigation systems, conjugate gradient algorithm, subtractive space search algorithm, dynamic error calibration

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