SINS初始对准QCDKF算法研究

郭凌云; 丁国强

doi:10.3969/j.issn.2095-476X.2013.01.021

CN 41-1437/TS ISSN 2096-1553

SINS初始对准QCDKF算法研究

郭凌云 , 丁国强

郭凌云, 丁国强. SINS初始对准QCDKF算法研究[J]. 轻工学报, 2013, 28(1): 86-91. doi: 10.3969/j.issn.2095-476X.2013.01.021

引用本文: 郭凌云, 丁国强. SINS初始对准QCDKF算法研究[J]. 轻工学报, 2013, 28(1): 86-91. doi: 10.3969/j.issn.2095-476X.2013.01.021

GUO Ling-yun and DING Guo-qiang. Quaternion central divided difference Kalman filtering algorithm in initial alignment of SINS[J]. Journal of Light Industry, 2013, 28(1): 86-91. doi: 10.3969/j.issn.2095-476X.2013.01.021

Citation: GUO Ling-yun and DING Guo-qiang. Quaternion central divided difference Kalman filtering algorithm in initial alignment of SINS[J]. Journal of Light Industry, 2013, 28(1): 86-91. doi: 10.3969/j.issn.2095-476X.2013.01.021

SINS初始对准QCDKF算法研究

郭凌云 ¹ ,
丁国强 ²

郑州轻工业学院外语系, 河南郑州 450002;
郑州轻工业学院电气信息工程学院, 河南郑州 450002
基金项目: 国家自然科学基金项目(U1204603)
中图分类号: V241.62⁺2;TP273⁺.5

Quaternion central divided difference Kalman filtering algorithm in initial alignment of SINS

GUO Ling-yun ¹ ,
DING Guo-qiang ²

Department of Foreign Languages, Zhengzhou University of Light Industry, Zhengzhou 450002, China;
College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
Received Date: 2012-02-17
Available Online: 2013-01-15
CLC number: V241.62⁺2;TP273⁺.5

摘要: 根据载体姿态四元数描述特点及其计算优势,建立了捷联惯导系统大失准角情形初始对准乘性四元数误差模型.该模型构造姿态矩阵代价函数计算其最大特征值,求取对应特征向量作为预测四元数均值并选择具有单位范数的特征向量来满足预测四元数均值计算保范性和符号不变性要求;利用乘性四元数误差表示四元数Sigma点与预测均值四元数间距,进而计算四元数预测误差方差矩阵.结合中心差分滤波(CDKF)算法提出四元数CDKF算法(QCDKF),实现大角度失准角情形的SINS初始对准仿真研究,与EKF算法相比,QCDKF算法数值计算稳定性较好,姿态误差角和速度误差滤波精度得到明显改善和提高.
- 捷联惯导 /
- 初始对准 /
- 四元数中心差分滤波 /
- 乘性误差四元数
Abstract: Considering the characteristics and computation superiority of quaternion representing body attitude movement, and aiming at the initial alignment procedure of strapdown inertial navigation system (SINS) with large initial misalignment angles,its multiplicative quaternion error model were developed. It proposes the new calculation method in which the attitude matrix cost function was constructed to calculate its maximum eigenvalues, and select the eigenvector which corresponds to the maximum eigenvalue as the predicted quaternion mean to guarantee its unit normalization and the sign invariability. The multiplicative quaternion error representing the distance between quaternion Sigma-points and the predicted quaternion mean calculates the quaternion prediction error variance matrix, which can effectively overcome the application limits for SPKF algorithms in quaternion filtering implementation. Combined with the central divided difference filtering (CDKF) algorithm, it proposes the new quaternion CDKF algorithm (QCDKF) for quaternion filtering problems in the SINS' simulation experiments. The simulations results showed that, compared with EKF algorithm, the proposed algorithm can significantly improve the filtering precision of both attitude misalignment angles and velocity and have better stabilization in the numerical calculation.
- strapdown inertial navigation system (SINS) /
- initial alignment /
- quaternion central divided difference filtering /
- multiplicative quaternion error
1. [1]
  Britting K R.Inertial Navigation System Analysis[M].NewYork:New York Wiley-Interscience,1971.
2. [2]
  Chung D Y,Lee J G.Comparison of SDINS in-flight alignment using equivalent error models[J].IEEE Transactions on Aerospace and Electronic Systems,1999,35(3):1046.
3. [3]
  Crassidis J L,Markley F L.Unscented filtering for spacecraft attitude estimation[J].Journal of Guidance Control and Dynamics,2003,26(4):536.
4. [4]
  Egziabher D G,Hayward R.Design of multi-sensor attitude determination systems[J].IEEE Transactions on Aerospace and Electronic Systems, 2004,40(2):627.
5. [5]
  Choukroun D,IBar-Itzhack,Oshman Y.Novel quaternion kalman filter[J].IEEE Transactions on Aerospace and Electronic Systems,2006,42(1):174.
6. [6]
  Markley F L,Cheng Y,Crassidis J L,et al.Averaging quaternions[J].Journal of Guidance Control and Dynamics,2007,30(4):1193.
7. [7]
  丁国强,周卫东,郝燕玲.传递对准系统乘性四元数误差模型的QCDKF滤波研究[J].华中科技大学学报:自然科学版,2010(8):86.
8. [8]
  丁国强,周卫东,郝燕玲.传递对准的MRP-CDKF算法[J].华中科技大学学报:自然科学版,2011(1):129.
9. [9]
  Oshman Y,Carmi A.Attitude estimation from vector observations using genetic-algorithm-embedded quaternion particle filter[J].Journal of Guidance Control and Dynamics,2006,29(4):879.
1. [1]
  吴晓东 , 刘畅 , 李俊 , 胡良志 , 贺凌晨 , 袁海霞 , 李强 , 黄锦标 . 基于高光谱检测的烟丝加香均匀性表征方法. 轻工学报, 2024, 39(5): 95-101. doi: 10.12187/2024.05.011
2. [2]
  刘广超 , 邓莎 , 高峄涵 , 吴涛 , 邓锐杰 . 加热卷烟辊压法薄片丝吸湿性影响因素研究. 轻工学报, 2024, 39(5): 109-117. doi: 10.12187/2024.05.013
3. [3]
  李艳坤 , 张伟 , 刘彦伶 . 数据融合策略在食用油真实性鉴别中的研究与应用进展. 轻工学报, 2024, 39(5): 50-59. doi: 10.12187/2024.05.006

点击查看大图

计量

PDF下载量: 27
文章访问数: 741
引证文献数: 0

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

郭凌云, 丁国强. SINS初始对准QCDKF算法研究[J]. 轻工学报, 2013, 28(1): 86-91. doi: 10.3969/j.issn.2095-476X.2013.01.021

引用本文: 郭凌云, 丁国强. SINS初始对准QCDKF算法研究[J]. 轻工学报, 2013, 28(1): 86-91. doi: 10.3969/j.issn.2095-476X.2013.01.021

SINS初始对准QCDKF算法研究

郭凌云 ¹
丁国强 ²

郑州轻工业学院外语系, 河南郑州 450002;
郑州轻工业学院电气信息工程学院, 河南郑州 450002

收稿日期: 2012-02-17
网络出版日期: 2013-01-15

基金项目: 国家自然科学基金项目(U1204603)

关键词:

摘要: 根据载体姿态四元数描述特点及其计算优势,建立了捷联惯导系统大失准角情形初始对准乘性四元数误差模型.该模型构造姿态矩阵代价函数计算其最大特征值,求取对应特征向量作为预测四元数均值并选择具有单位范数的特征向量来满足预测四元数均值计算保范性和符号不变性要求;利用乘性四元数误差表示四元数Sigma点与预测均值四元数间距,进而计算四元数预测误差方差矩阵.结合中心差分滤波(CDKF)算法提出四元数CDKF算法(QCDKF),实现大角度失准角情形的SINS初始对准仿真研究,与EKF算法相比,QCDKF算法数值计算稳定性较好,姿态误差角和速度误差滤波精度得到明显改善和提高.

English Abstract

Quaternion central divided difference Kalman filtering algorithm in initial alignment of SINS

GUO Ling-yun ¹
DING Guo-qiang ²

Department of Foreign Languages, Zhengzhou University of Light Industry, Zhengzhou 450002, China;
College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China

Received Date: 2012-02-17
Available Online: 2013-01-15

Abstract: Considering the characteristics and computation superiority of quaternion representing body attitude movement, and aiming at the initial alignment procedure of strapdown inertial navigation system (SINS) with large initial misalignment angles,its multiplicative quaternion error model were developed. It proposes the new calculation method in which the attitude matrix cost function was constructed to calculate its maximum eigenvalues, and select the eigenvector which corresponds to the maximum eigenvalue as the predicted quaternion mean to guarantee its unit normalization and the sign invariability. The multiplicative quaternion error representing the distance between quaternion Sigma-points and the predicted quaternion mean calculates the quaternion prediction error variance matrix, which can effectively overcome the application limits for SPKF algorithms in quaternion filtering implementation. Combined with the central divided difference filtering (CDKF) algorithm, it proposes the new quaternion CDKF algorithm (QCDKF) for quaternion filtering problems in the SINS' simulation experiments. The simulations results showed that, compared with EKF algorithm, the proposed algorithm can significantly improve the filtering precision of both attitude misalignment angles and velocity and have better stabilization in the numerical calculation.

参考文献 (9) 相关文章 (3)