ISR-CDKF在SINS大方位失准角初始对准中的应用

J4 ›› 2013, Vol. 31 ›› Issue (2): 196-202.

ISR-CDKF在SINS大方位失准角初始对准中的应用

贾鹤鸣¹, 宋文龙¹, 牟宏伟², 车延庭³

1. 东北林业大学机电工程学院, 哈尔滨 150040； 2. 中国运载火箭技术研究院, 北京100076；3. 哈尔滨工程大学自动化学院, 哈尔滨 150001

收稿日期:2012-11-01 出版日期:2013-03-23 发布日期:2013-06-05
作者简介:贾鹤鸣(1983—), 男, 哈尔滨人, 东北林业大学副教授, 博士, 主要从事非线性系统控制理论与应用、智能控制与滤波技术方面的研究, (Tel)13206666920(E-mail)jiaheminglucky99@126.com|通信作者：宋文龙(1973—), 男, 吉林四平人, 东北林业大学教授, 博导, 主要从事林业智能检测与控制方面的研究(Tel)13206666921(Email)wlsong139@126.com。
基金资助:
国家自然科学基金资助项目(30972424)；教育部新世纪优秀人才支持计划基金资助项目(NCET-10-0279)

Application of ISR-CDKF in Initial Alignment of Large Azimuth Misalignment in the SINS

JIA He-ming¹, SONG Wen-long¹, MU Hong-wei², CHE Yan-ting³

1. College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China；2. China Academy of Launch Vehicle Technology, Beijing 100076, China;3. College of Automation,Harbin Engineering University, Harbin 150001, China

Received:2012-11-01 Online:2013-03-23 Published:2013-06-05

摘要/Abstract

摘要：

针对捷联惯导系统（SINS: Strapdown Inertial Navigation System）误差模型在大方位失准角条件下非线性的特点, 对非线性滤波算法的研究具有十分重要的意义。扩展卡尔曼滤波（EKF: Extended Kalman Filter）精度低, 而且需要计算复杂的雅可比（Jacobian）矩阵；而中心差分卡尔曼滤波（CDKF: Central Difference Kalman Filter）虽然精度稍高, 但计算量大, 且算法不稳定。为克服以上不足, 提出了迭代测量更新的平方根中心差分卡尔曼滤波(ISRCDKF: Iterative Square Root Central Difference Kalman Filter)算法, 并应用于SINS大方位初始对准中。通过滤波仿真, 进一步表明了ISRCDKF算法不仅具有更高的精度和收敛性, 同时具有较强的数值稳定性。

关键词: 大方位失准角, 捷联惯导, 初始对准, ISR-CDKF算法

Abstract:

In case of that the error model of the strapdown inertial navigation system is nonlinear with large azimuth misalignment, it is very significant to study the nonlinear filter algorithm. The precision of EKF (Extended Kalman Filter) is low, which needs to calculate the complex Jacobian matrices. Although the theoretical precision of CDKF (Central Difference Kalman Filter) is a little higher, the amount of calculation is large and the algorithm is unstable. To overcome the above shortcomings, the ISR-CDKF (Iterative Square Root Central Difference Kalman Filter) is proposed, and is utilized in initial alignment. The results of simulation show that the ISR-CDKF has higher precision and convergence, and has stronger numerical stability.

Key words: large azimuth misalignment, strapdown inertial navigation system, initial alignment, iterative square root central difference kalman filter (ISR-CDKF)

中图分类号:

U666.1

贾鹤鸣, 宋文龙, 牟宏伟, 车延庭. ISR-CDKF在SINS大方位失准角初始对准中的应用[J]. J4, 2013, 31(2): 196-202.

JIA He-ming, SONG Wen-long, MU Hong-wei, CHE Yan-ting. Application of ISR-CDKF in Initial Alignment of Large Azimuth Misalignment in the SINS[J]. J4, 2013, 31(2): 196-202.