ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Criterion MP-S for multi-scale cascaded geomagnetic matching similarity measurement
Received date: 2024-01-15
Revised date: 2024-03-21
Accepted date: 2024-04-08
Online published: 2024-04-10
Supported by
National Natural Science Foundation of China(42204048)
Geomagnetic matching positioning has the advantages of being passive， covert， and free from cumulative errors， showing broad prospects of application in the military field. The core of geomagnetic matching positioning is to determine the current position of the carrier by measuring the similarity between the measured geomagnetic field sequence and the target sequence in the geomagnetic reference map. However， existing criteria for geomagnetic matching similarity measurement do not fully consider the global and detailed features of the magnetic sequence， and are easily affected by magnetic field disturbances. To address these limitations， this paper proposes a Matrix Profile-Space （MP-S） criterion based on the Matrix Profile （MP） algorithm to achieve measurement of multi-scale cascading geomagnetic matching similarity. A Nearest Neighbor-Space （NN-S） function is constructed based on cascade detailed features and global space constraints， effectively filtering out incorrectly matched detailed features of magnetic sequences， thereby improving positioning accuracy and fault tolerance. Additionally， we design a lightweight 2D-Magnetic Light （2D-MLight） search and calculation strategy to address the complex computation issues of the MP algorithm， significantly reducing the runtime of the similarity measurement algorithm by avoiding redundant similarity calculations of adjacent target sequences. The processing results of geomagnetic data from a certain aircraft show that using the MP-S criterion for similarity measurement results in a horizontal positioning error of 48.6 m and a matching probability of 93.99%， outperforming the commonly used Mean Square-Difference （MSD） criterion. Furthermore， the lightweight search and calculation process of 2D-MLight can meet real-time positioning requirements， demonstrating good engineering application significance for improving the performance of magnetic matching positioning in complex scenarios with flat features and local disturbances.
Yixuan YOU , Xinchun JI , Dongyan WEI , Yi LU , Hong YUAN . Criterion MP-S for multi-scale cascaded geomagnetic matching similarity measurement[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2024 , 45(21) : 330149 -330149 . DOI: 10.7527/S1000-6893.2024.30149
| 1 | CHEN Z， LIU K J， ZHANG Q， et al. Geomagnetic vector pattern recognition navigation method based on probabilistic neural network［J］. IEEE Transactions on Geoscience and Remote Sensing， 2023， 61： 5909608. |
| 2 | CHEN Z， LIU Z Y， ZHANG Q， et al. An improved geomagnetic navigation method based on two-component gradient weighting［J］. IEEE Geoscience and Remote Sensing Letters， 2022， 19： 8030005. |
| 3 | WANG L Y， LUO H Y， WANG Q， et al. A hierarchical LSTM-based indoor geomagnetic localization algorithm［J］. IEEE Sensors Journal， 2022， 22（2）： 1227-1237. |
| 4 | 高东， 朱明慧， 韩鹏. 一种地磁/惯性深度融合导航方法［J］. 中国惯性技术学报， 2022， 30（4）： 437-444. |
| GAO D， ZHU M H， HAN P. A geomagnetic/inertial depth fusion navigation method［J］. Journal of Chinese Inertial Technology， 2022， 30（4）： 437-444 （in Chinese）. | |
| 5 | PANG Y， ZHOU Z， PAN X， et al. An INS/geomagnetic integrated navigation method for coarse estimation of positioning error and search area adaption applied to high-speed aircraft［J］. IEEE Sensors Journal， 2023， 23（7）： 7766-7775. |
| 6 | 陆一， 魏东岩， 纪新春， 等. 地磁定位方法综述［J］. 导航定位与授时， 2022， 9（2）： 118-130. |
| LU Y， WEI D Y， JI X C， et al. Review of geomagnetic positioning method［J］. Navigation Positioning and Timing， 2022， 9（2）： 118-130 （in Chinese）. | |
| 7 | REN Y， WANG L H， LIN K J， et al. Improved iterative closest contour point matching navigation algorithm based on geomagnetic vector［J］. Electronics， 2022， 11（5）： 796. |
| 8 | QI X K， XU K W， XU Z W， et al. Geographic true navigation based on real-time measurements of geomagnetic fields［J］. IEEE Transactions on Geoscience and Remote Sensing， 2023， 61： 5917810. |
| 9 | YU H P， LI Z Y， YANG W T， et al. Underwater geomagnetic localization based on adaptive fission particle-matching technology［J］. Journal of Marine Science and Engineering， 2023， 11（9）： 1739. |
| 10 | CHEN K， LIANG W C， LIU M X， et al. Comparison of geomagnetic aided navigation algorithms for hypersonic vehicles［J］. Journal of Zhejiang University： Science A， 2020， 21（8）： 673-683. |
| 11 | 邓翠婷， 黄朝艳， 赵华， 等. 地磁匹配导航算法综述［J］. 科学技术与工程， 2012， 12（24）： 6125-6131. |
| DENG C T， HUANG C Y， ZHAO H， et al. Review of geomagnetic matching navigation algorithm［J］. Science Technology and Engineering， 2012， 12（24）： 6125-6131 （in Chinese）. | |
| 12 | 肖晶， 齐晓慧， 段修生. 地磁匹配算法的研究现状及改进策略［J］. 电光与控制， 2018， 25（1）： 55-59， 73. |
| XIAO J， QI X H， DUAN X S. Research status of magnetic matching algorithm and its improvement strategies［J］. Electronics Optics & Control， 2018， 25（1）： 55-59， 73 （in Chinese）. | |
| 13 | 贾磊， 王跃钢， 单斌， 等. 基于增强型MAD单特征量地磁匹配导航算法［J］. 现代防御技术， 2012， 40（1）： 90-94. |
| JIA L， WANG Y G， SHAN B， et al. Simulation of single element geomagnetic matching navigation based on intensified MAD［J］. Modern Defence Technology， 2012， 40（1）： 90-94 （in Chinese）. | |
| 14 | 付希禹， 孙永荣， 李荣冰. 基于MSD和ICCP改进的地磁联合匹配算法［J］. 南京航空航天大学学报， 2021， 53（6）： 928-933. |
| FU X Y， SUN Y R， LI R B. Improved geomagnetic united matching algorithm based on MSD and ICCP［J］. Journal of Nanjing University of Aeronautics & Astronautics， 2021， 53（6）： 928-933 （in Chinese）. | |
| 15 | 赵龙， 颜廷君. 不同传感器精度下的地形辅助导航系统性能评估［J］. 北京航空航天大学学报， 2013， 39（8）： 1016-1019. |
| ZHAO L， YAN T J. Performance evaluation of a terrain-aided navigation system under different accuracy of sensor［J］. Journal of Beijing University of Aeronautics and Astronautics， 2013， 39（8）： 1016-1019 （in Chinese）. | |
| 16 | 伏潜， 朱跃龙， 万定生. 交叉熵相似性度量在水文时间序列匹配中的应用［J］. 计算机与数字工程， 2015， 43（2）： 164-167. |
| FU Q， ZHU Y L， WAN D S. Application of similarity measure of cross entropy in hydrological time series［J］. Computer & Digital Engineering， 2015， 43（2）： 164-167 （in Chinese）. | |
| 17 | 胡鹏， 周学文. 基于地磁熵及灰关联分析的地磁匹配新方法［J］. 舰船电子工程， 2012， 32（5）： 68-70. |
| HU P， ZHOU X W. A new geomagnetic localization algorithm based on geomagnetic entropy and grey correlation analysis［J］. Ship Electronic Engineering， 2012， 32（5）： 68-70 （in Chinese）. | |
| 18 | GUO C F， CAI H， VAN DER HEIJDEN G H M. Feature extraction and geomagnetic matching［J］. Journal of Navigation， 2013， 66（6）： 799-811. |
| 19 | CHEN Y Y， ZHOU M X， ZHENG Z W. Learning sequence-based fingerprint for magnetic indoor positioning system［J］. IEEE Access， 2019， 7： 163231-163244. |
| 20 | SHU M C， CHEN G L， ZHANG Z H， et al. Indoor geomagnetic positioning using direction-aware multiscale recurrent neural networks［J］. IEEE Sensors Journal， 2023， 23（3）： 3321-3333. |
| 21 | YEH C C M， ZHU Y， ULANOVA L， et al. Matrix profile I： All pairs similarity joins for time series： A unifying view that includes motifs， discords and shapelets［C］∥ 2016 IEEE 16th International Conference on Data Mining （ICDM）. Piscataway： IEEE Press， 2016： 1317-1322. |
| 22 | ZHU Y， ZIMMERMAN Z， SENOBARI N S， et al. Matrix profile II： Exploiting a novel algorithm and GPUs to break the one hundred million barrier for time series motifs and joins［C］∥2016 IEEE 16th International Conference on Data Mining （ICDM）. Piscataway： IEEE Press， 2016： 739-748. |
| 23 | GHARGHABI S， IMANI S， BAGNALL A， et al. Matrix profile XII： MPdist： A novel time series distance measure to allow data mining in more challenging scenarios［C］∥ 2018 IEEE International Conference on Data Mining （ICDM）. Piscataway： IEEE Press， 2018： 965-970. |
| 24 | GHARGHABI S， IMANI S， BAGNALL A， et al. An ultra-fast time series distance measure to allow data mining in more complex real-world deployments［J］. Data Mining and Knowledge Discovery， 2020， 34（4）： 1104-1135. |
| 25 | KADIO?LU T， ERKMEN B. BASISMAP： Sequence-based similarity search for geomagnetic positioning［J］. Turkish Journal of Electrical Engineering and Computer Sciences， 2023， 31（1）： 146-162. |
| 26 | 崔志强， 胥值礼， 李军峰， 等. 无人机航空物探技术研发应用现状与展望［J］. 物探化探计算技术， 2016， 38（6）： 740-745. |
| CUI Z Q， XU Z L， LI J F， et al. The R & D application of UAV airborne geophysical survey and its development trend［J］. Computing Techniques for Geophysical and Geochemical Exploration， 2016， 38（6）： 740-745 （in Chinese）. | |
| 27 | 张秀玲， 范晓勇， 周江林. 北京地磁场变化特征分析［J］. 地震地磁观测与研究， 2015， 36（6）： 43-47. |
| ZHANG X L， FAN X Y， ZHOU J L. Analysis on variation characteristics of geomagnetic field in Beijing area［J］. Seismological and Geomagnetic Observation and Research， 2015， 36（6）： 43-47 （in Chinese）. |
/
| 〈 |
|
〉 |
CJA