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基于 SINS/CNS 深度融合模式的弹道导弹导航系统的最大 corrrentropy 无迹卡尔曼滤波。

Maximum Correntropy Unscented Kalman Filter for Ballistic Missile Navigation System based on SINS/CNS Deeply Integrated Mode.

机构信息

Department of System Science, College of Liberal Arts and Science, National University of Defense Technology, Fuyuan Road No.1, Changsha 410072, China.

Beijing Institute of Control Engineering, China Academy of Space Technology, Beijing 100080, China.

出版信息

Sensors (Basel). 2018 May 27;18(6):1724. doi: 10.3390/s18061724.

DOI:10.3390/s18061724
PMID:29861489
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6022141/
Abstract

Strap-down inertial navigation system/celestial navigation system ( SINS/CNS) integrated navigation is a high precision navigation technique for ballistic missiles. The traditional navigation method has a divergence in the position error. A deeply integrated mode for SINS/CNS navigation system is proposed to improve the navigation accuracy of ballistic missile. The deeply integrated navigation principle is described and the observability of the navigation system is analyzed. The nonlinearity, as well as the large outliers and the Gaussian mixture noises, often exists during the actual navigation process, leading to the divergence phenomenon of the navigation filter. The new nonlinear Kalman filter on the basis of the maximum correntropy theory and unscented transformation, named the maximum correntropy unscented Kalman filter, is deduced, and the computational complexity is analyzed. The unscented transformation is used for restricting the nonlinearity of the system equation, and the maximum correntropy theory is used to deal with the non-Gaussian noises. Finally, numerical simulation illustrates the superiority of the proposed filter compared with the traditional unscented Kalman filter. The comparison results show that the large outliers and the influence of non-Gaussian noises for SINS/CNS deeply integrated navigation is significantly reduced through the proposed filter.

摘要

捷联惯性导航系统/天文导航系统（SINS/CNS）组合导航是一种高精度的弹道导弹导航技术。传统的导航方法存在位置误差发散的问题。为了提高弹道导弹的导航精度，提出了一种捷联惯性导航系统/天文导航系统的深度组合导航模式。描述了深度组合导航原理，分析了导航系统的可观性。在实际导航过程中，往往存在非线性、大野值和高斯混合噪声，导致导航滤波器发散现象。基于最大相关熵理论和无迹变换推导出了新的非线性卡尔曼滤波器，命名为最大相关熵无迹卡尔曼滤波器，并对其计算复杂度进行了分析。无迹变换用于限制系统方程的非线性，最大相关熵理论用于处理非高斯噪声。最后，数值仿真说明了与传统无迹卡尔曼滤波器相比，所提出的滤波器的优越性。比较结果表明，通过所提出的滤波器可以显著降低 SINS/CNS 深度组合导航中大野值和非高斯噪声的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/6b8aa631b4de/sensors-18-01724-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/cdc832723cd6/sensors-18-01724-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/f4a62be0cffc/sensors-18-01724-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/96e7a7e6cef7/sensors-18-01724-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/15d96ce8d9c3/sensors-18-01724-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/5eba2bd01640/sensors-18-01724-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/c8287901b2e5/sensors-18-01724-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/5afc684749af/sensors-18-01724-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/4c1e1e3cf3dc/sensors-18-01724-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/96398c7e135a/sensors-18-01724-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/6b8aa631b4de/sensors-18-01724-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/cdc832723cd6/sensors-18-01724-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/54b22e50d4e9/sensors-18-01724-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/5b5f880769f2/sensors-18-01724-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/1ceb8f76752e/sensors-18-01724-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/f4a62be0cffc/sensors-18-01724-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/96e7a7e6cef7/sensors-18-01724-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/15d96ce8d9c3/sensors-18-01724-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/5eba2bd01640/sensors-18-01724-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/c8287901b2e5/sensors-18-01724-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/5afc684749af/sensors-18-01724-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/4c1e1e3cf3dc/sensors-18-01724-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/96398c7e135a/sensors-18-01724-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec3a/6022141/6b8aa631b4de/sensors-18-01724-g013.jpg

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Maximum Correntropy Unscented Kalman Filter for Spacecraft Relative State Estimation.用于航天器相对状态估计的最大互信息无迹卡尔曼滤波器
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