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高斯混合模型优化的四元数约束CKF姿态估计
引用本文:戴卿,隋立芬,田源,曾添,田翌君. 高斯混合模型优化的四元数约束CKF姿态估计[J]. 宇航学报, 2018, 39(8): 913-919. DOI: 10.3873/j.issn.1000-1328.2018.08.011
作者姓名:戴卿  隋立芬  田源  曾添  田翌君
作者单位:信息工程大学地理空间信息学院,郑州 450001
基金项目:国家自然科学基金(41674016;41274016)
摘    要:针对四元数非线性滤波在姿态估计中噪声为非理想高斯分布时随机模型的失配现象,提出了一种基于高斯混合模型的四元数约束容积卡尔曼滤波(GM-QCKF)。讨论了四元数在容积卡尔曼滤波中的加权均值方法,并利用高斯混合模型对高斯分量更新与求和从而精化随机模型,最后通过两步投影理论做归一化限制,有效地改进了四元数约束容积卡尔曼滤波的稳定性。通过仿真测试,表明GM-QCKF可明显提高姿态估计精度;跑车试验验证了GM-QCKF算法在实际应用中精度和稳定性的优势。

关 键 词:四元数约束  容积卡尔曼滤波  非高斯噪声  高斯混合滤波  姿态估计  
收稿时间:2017-11-09

Quaternion Constrained Cubature Kalman Filter Attitude Estimation Based on Gaussian Mixture Model
DAI Qing,SUI Li fen,TIAN Yuan,ZENG Tian,TIAN Yi jun. Quaternion Constrained Cubature Kalman Filter Attitude Estimation Based on Gaussian Mixture Model[J]. Journal of Astronautics, 2018, 39(8): 913-919. DOI: 10.3873/j.issn.1000-1328.2018.08.011
Authors:DAI Qing  SUI Li fen  TIAN Yuan  ZENG Tian  TIAN Yi jun
Affiliation:Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China
Abstract:A quaternion cubature Kalman filter improved by the Gaussian mixture model (GM-QCKF) is proposed to solve the model mismatch problem of a quaternion nonlinear filter with non-gaussian noise distribution in attitude estimation. The weighted mean algorithm of quaternion based CKF is discussed; every gaussian component is updated and summed by the gaussian mixture model to refine the stochastic model; and the normalization is obtained by the two-step projection theory. These improvements make quaternion nonlinear updating algorithm more stable. The simulation comparison experiments show that the GM-QCKF can improve the precision of the attitude estimation. And the car trial experiment is conducted. The results indicate that compared with the traditional algorithm the GM-QCKF is superior in accuracy and stability.
Keywords:Quaternion constraint  Cubature Kalman filter  Non gaussian noise  Gaussian mixture filter  Attitude estimation  
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