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CLC number: V44

On-line Access: 2021-05-12

Received: 2020-11-09

Revision Accepted: 2021-03-15

Crosschecked: 2021-04-14

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Kai Chen

https://orcid.org/0000-0002-2586-7546

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Journal of Zhejiang University SCIENCE A 2021 Vol.22 No.5 P.357-368

http://doi.org/10.1631/jzus.A2000524


Multi-geomagnetic-component assisted localization algorithm for hypersonic vehicles


Author(s):  Kai Chen, Wen-chao Liang, Cheng-zhi Zeng, Rui Guan

Affiliation(s):  School of Astronautics, Northwestern Polytechnical University, Xian 710072, China; more

Corresponding email(s):   chenkai@nwpu.edu.cn

Key Words:  Geomagnetic navigation, Isopleth, Geomagnetic components, Integrated navigation, Ká, lmá, n filter


Kai Chen, Wen-chao Liang, Cheng-zhi Zeng, Rui Guan. Multi-geomagnetic-component assisted localization algorithm for hypersonic vehicles[J]. Journal of Zhejiang University Science A, 2021, 22(5): 357-368.

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author="Kai Chen, Wen-chao Liang, Cheng-zhi Zeng, Rui Guan",
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pages="357-368",
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T1 - Multi-geomagnetic-component assisted localization algorithm for hypersonic vehicles
A1 - Kai Chen
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DOI - 10.1631/jzus.A2000524


Abstract: 
Owing to the lack of information about geomagnetic anomaly fields, conventional geomagnetic matching algorithms in near space are prone to divergence. Therefore, geomagnetic matching navigation algorithms for hypersonic vehicles are also prone to divergence or mismatch. To address this problem, we propose a multi-geomagnetic-component assisted localization (MCAL) algorithm to improve positioning accuracy using only the information of the main geomagnetic field. First, the main components of the geomagnetic field and a mathematical representation of the Earth’s geomagnetic field (World Magnetic Model 2015) are introduced. The mathematical relationships between the geomagnetic components are given, and the source of geomagnetic matching error is explained. We then propose the MCAL algorithm. The algorithm uses the intersections of the isopleths of the geomagnetic components and a decision method to estimate the real position of a carrier with high positioning accuracy. Finally, inertial/geomagnetic integrated navigation is simulated for hypersonic boost-glide vehicles. The simulation results demonstrate that the proposed algorithm can provide higher positioning accuracy than conventional geomagnetic matching algorithms. When the random error range is ±30 nT, the average absolute latitude error and longitude error of the MCAL algorithm are 151 m and 511 m lower, respectively, than those of the Sandia inertial magnetic aided navigation (SIMAN) algorithm.

高超声速飞行器多地磁分量辅助定位算法

目的:改善高超声速飞行器由于地磁异常信息缺失导致的地磁匹配算法发散或失配等问题.
创新点:提出一种多地磁分量辅助定位(MCAL)算法,并在助推-滑翔高超声速飞行器弹道上进行仿真验证.
方法:1. 给出地磁主磁场模型的数学表达,分析地磁匹配系统的误差来源.2. 从理想情况出发,提出一种MCAL算法,并通过2~3条地磁分量的等值线对飞行器位置进行估计.3. 在助推-滑翔高超声速飞行器弹道上进行数字仿真试验,并与其他几种传统算法进行分析比较.
结论:该方法相较于传统算法具有更高的定位精度.当随机误差范围为±30 nT(每轴)时,MCAL算法的平均绝对纬度误差比SIMAN算法低151 m,经度误差比SIMAN算法低511 m.

关键词:地磁导航;等值线;地磁分量;组合导航;卡尔曼滤波

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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