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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


Kai Chen


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


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, Xi’an 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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journal="Journal of Zhejiang University Science A",
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%T Multi-geomagnetic-component assisted localization algorithm for hypersonic vehicles
%A Kai Chen
%A Wen-chao Liang
%A Cheng-zhi Zeng
%A Rui Guan
%J Journal of Zhejiang University SCIENCE A
%V 22
%N 5
%P 357-368
%@ 1673-565X
%D 2021
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2000524

T1 - Multi-geomagnetic-component assisted localization algorithm for hypersonic vehicles
A1 - Kai Chen
A1 - Wen-chao Liang
A1 - Cheng-zhi Zeng
A1 - Rui Guan
J0 - Journal of Zhejiang University Science A
VL - 22
IS - 5
SP - 357
EP - 368
%@ 1673-565X
Y1 - 2021
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2000524

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.


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.


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


[1]Chen K, Zhang LY, Wang X, et al., 2017. Strapdown inertial navigation algorithm for hypersonic boost-glide vehicle. Proceedings of the 21st AIAA International Space Planes and Hypersonics Technologies Conference.

[2]Chen K, Shen FQ, Sun HY, et al., 2019. Hypersonic vehicle navigation algorithm in launch centered Earth-fixed frame. Journal of Astronautics, 40(10):1212-1218 (in Chinese).

[3]Chen K, Liang WC, Liu MX, et al., 2020a. Comparison of geomagnetic aided navigation algorithms for hypersonic vehicles. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 21(8):673-683.

[4]Chen K, Zhou J, Shen FQ, et al., 2020b. Hypersonic boost–glide vehicle strapdown inertial navigation system/ global positioning system algorithm in a launch-centered Earth-fixed frame. Aerospace Science and Technology, 98:105679.

[5]Chen Z, Zhang Q, Pan MC, et al., 2018. A new geomagnetic matching navigation method based on multidimensional vector elements of Earth’s magnetic field. IEEE Geoscience and Remote Sensing Letters, 15(8):1289-1293.

[6]Chulliat A, Macmillan S, Alken P, et al., 2015. The US/UK World Magnetic Model for 2015-2020. Technical Report, National Geophysical Data Center, NOAA, USA.

[7]Cui F, Gao D, Zheng JH, 2020. Magnetometer-based autonomous orbit determination via a measurement differencing extended Kalman filter during geomagnetic storms. Aircraft Engineering and Aerospace Technology, 92(3):428-439.

[8]Dong CY, Liu C, Wang Q, et al., 2019. Switched adaptive active disturbance rejection control of variable structure near space vehicles based on adaptive dynamic programming. Chinese Journal of Aeronautics, 32(7):1684-1694.

[9]Duan XS, Xiao J, Qi XH, et al., 2019. An INS/geomagnetic integrated navigation algorithm based on matching strategy and hierarchical filtering. Electronics, 8(4):460.

[10]Goldenberg F, 2006. Geomagnetic navigation beyond the magnetic compass. IEEE/ION Position, Location, and Navigation Symposium, p.684-694.

[11]Harsha PBS, Ratnam DV, 2020. Generation of regional ionospheric TEC maps with EIA nowcasting/forecasting capability during geomagnetic storm conditions. IEEE Access, 8:57879-57890.

[12]He RG, Hu XP, Zhang LL, et al., 2019. A combination orientation compass based on the information of polarized skylight/geomagnetic/MIMU. IEEE Access, 8:10879-10887.

[13]Heimpel MH, Evans ME, 2013. Testing the geomagnetic dipole and reversing dynamo models over Earth’s cooling history. Physics of the Earth and Planetary Interiors, 224: 124-131.

[14]Hu GG, Gao BB, Zhong YM, et al., 2019. Robust unscented Kalman filtering with measurement error detection for tightly coupled INS/GNSS integration in hypersonic vehicle navigation. IEEE Access, 7:151409-151421.

[15]Li H, Liu MY, Zhang FH, 2017. Geomagnetic navigation of autonomous underwater vehicle based on multi-objective evolutionary algorithm. Frontiers in Neurorobotics, 11: 34.

[16]Li LM, 2013. Research on Algorithm of Geomagnetic Navigation System. MS Thesis, Harbin Institute of Technology, Harbin, China (in Chinese).

[17]Li SJ, Lei HM, Shao L, et al., 2019. Multiple model tracking for hypersonic gliding vehicles with aerodynamic modeling and analysis. IEEE Access, 7:28011-28018.

[18]Liu MY, Wang PX, Guo JJ, et al., 2019. Research on geomagnetic navigation and positioning algorithm based on full-connected constraints for AUV. OCEANS 2019-Marseille, p.1-5.

[19]Lv Z, Xia ZX, Liu B, et al., 2017. Preliminary experimental study on solid-fuel rocket scramjet combustor. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 18(2):106-112.

[20]NCEI (National Centers for Environmental Information), 2019. The world magnetic model. NCEI, USA. https://www.ngdc.noaa.gov/geomag/WMM/index.html

[21]Qi XK, Ye DX, Sun YZ, et al., 2017. Simulations to true animals’ long-distance geomagnetic navigation. IEEE Transactions on Magnetics, 53(1):5200108.

[22]Shen BX, Liu HP, Liu WQ, 2020. Influence of angle of attack on a combined opposing jet and platelet transpiration cooling blunt nose in hypersonic vehicle. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 21(9):761-769.

[23]Song ZG, Zhang JS, Zhu WQ, et al., 2016. The vector matching method in geomagnetic aiding navigation. Sensors, 16(7):1120.

[24]Wang JH, Guo YF, Guo LW, et al., 2019. Performance test of MPMD matching algorithm for geomagnetic and RFID combined underground positioning. IEEE Access, 7: 129789-129801.

[25]Wang Q, Zhou J, 2019. Triangle matching method for the sparse environment of geomagnetic information. Optik, 181:651-658.

[26]Wang WK, Hou ZX, Shan SQ, et al., 2019. Periodically cruising hypersonic vehicle with active cooling: an optimal-control based design approach. IEEE Access, 7: 65486-65505.

[27]Wang YY, Yang XX, Yan HC, 2019. Reliable fuzzy tracking control of near-space hypersonic vehicle using aperiodic measurement information. IEEE Transactions on Industrial Electronics, 66(12):9439-9447.

[28]Wei WH, Gao ZH, Gao SS, et al., 2018. A SINS/SRS/GNS autonomous integrated navigation system based on spectral redshift velocity measurements. Sensors, 18(4):1145.

[29]Xia RS, Wu QX, Chen M, 2019. Disturbance observer-based optimal longitudinal trajectory control of near space vehicle. Science China Information Sciences, 62(5):50212.

[30]Xiao J, Duan XS, Qi XH, et al., 2020. An improved ICCP matching algorithm for use in an interference environment during geomagnetic navigation. The Journal of Navigation, 73(1):56-74.

[31]Yang C, Zhao HD, Wu ZG, 2019. Research progress of aerothermoelasticity of air-breathing hypersonic vehicles. Journal of Beijing University of Aeronautics and Astronautics, 45(10):1911-1923 (in Chinese).

[32]Zong H, Liu Y, Yang Y, 2018. Overview of the research status about geomagnetic navigation technology. Aerospace Control, 36(3):93-98 (in Chinese).

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