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基于互补滤波器的航天飞机捷联惯性导航系统/天文导航系统/全球定位系统组合导航系统信息融合

Information Fusion Based on Complementary Filter for SINS/CNS/GPS Integrated Navigation System of Aerospace Plane.

作者信息

Zhao Yanming, Yan Gongmin, Qin Yongyuan, Fu Qiangwen

机构信息

School of Automation, Northwestern Polytechnical University, Xi'an 710129, China.

出版信息

Sensors (Basel). 2020 Dec 15;20(24):7193. doi: 10.3390/s20247193.

DOI:10.3390/s20247193
PMID:33333963
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7765422/
Abstract

In order to solve the problems of heavy computational load and poor real time of the information fusion method based on the federated Kalman filter (FKF), a novel information fusion method based on the complementary filter is proposed for strapdown inertial navigation (SINS)/celestial navigation system (CNS)/global positioning system (GPS) integrated navigation system of an aerospace plane. The complementary filters are designed to achieve the estimations of attitude, velocity, and position in the SINS/CNS/GPS integrated navigation system, respectively. The simulation results show that the proposed information fusion method can effectively realize SINS/CNS/GPS information fusion. Compared with FKF, the method based on complementary filter (CF) has the advantages of simplicity, small calculation, good real-time performance, good stability, no need for initial alignment, fast convergence, etc. Furthermore, the computational efficiency of CF is increased by 94.81%. Finally, the superiority of the proposed CF-based method is verified by both the semi-physical simulation and real-time system experiment.

摘要

为了解决基于联邦卡尔曼滤波器（FKF）的信息融合方法计算负荷重、实时性差的问题，针对航天飞机捷联惯性导航系统（SINS）/天文导航系统（CNS）/全球定位系统（GPS）组合导航系统，提出了一种基于互补滤波器的新型信息融合方法。设计互补滤波器分别实现SINS/CNS/GPS组合导航系统中姿态、速度和位置的估计。仿真结果表明，所提出的信息融合方法能够有效实现SINS/CNS/GPS信息融合。与FKF相比，基于互补滤波器（CF）的方法具有简单、计算量小、实时性好、稳定性好、无需初始对准、收敛速度快等优点。此外，CF的计算效率提高了94.81%。最后，通过半物理仿真和实时系统实验验证了所提基于CF方法的优越性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6c5/7765422/5b32793d4dc2/sensors-20-07193-g017.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6c5/7765422/5b32793d4dc2/sensors-20-07193-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6c5/7765422/c9caec353720/sensors-20-07193-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6c5/7765422/fb936a54aca5/sensors-20-07193-g009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6c5/7765422/e443ab107568/sensors-20-07193-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6c5/7765422/15d7a40843d3/sensors-20-07193-g012.jpg
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