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

[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).