{"id":6539,"date":"2026-06-20T20:22:50","date_gmt":"2026-06-20T12:22:50","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=6539"},"modified":"2026-07-24T14:34:54","modified_gmt":"2026-07-24T06:34:54","slug":"integrating-sins-sensors-with-odometer-measurements-for-land-vehicle-navigation-system","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=integrating-sins-sensors-with-odometer-measurements-for-land-vehicle-navigation-system","title":{"rendered":"Integrating SINS Sensors with Odometer Measurements for Land Vehicle Navigation System"},"content":{"rendered":"\n
\n
\n

<\/i> 2019<\/a><\/p>\n<\/div>\n\n\n\n

\n

<\/i> Volume 22, Issue 2<\/a><\/p>\n<\/div>\n\n\n\n

\n
\n
\n
\n

Susu Fang, Zengcai Wang<\/i><\/a> and Jiacheng Fan<\/p>\n\n\n\n

Key Laboratory of High-efficiency and Clean Mechanical Manufacture, Ministry of Education, College of Mechanical Engineering, Shandong University, Jinan, P.R. China<\/p>\n<\/div>\n\n\n\n

\n

Received:\u00a0April 09, 2018
Accepted: December 07, 2018
Publication Date:\u00a0June 20, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

\"\u4e0a\u50b3\u5716\u7247\"\n\n\n

Schematic of the frame coordinates.<\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation:  BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.201906_22(2).0009<\/a>  <\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

<\/div>\n\n\n\n

This paper details a new model for land vehicle navigation including attitude, velocity, and position estimation using an odometer (OD) and a magnetometer (MAG) in conjunction with strapdown inertial navigation system (SINS) sensors. In this new model, the SINS\/OD navigation system is designed firstly. In SINS\/OD system, the application of non-holonomic constraints for obtaining virtual velocity measurements is investigated and an innovation-based estimation adaptive (IAE) Kalman filter is designed to provide a land vehicle navigation solution by combining the velocity measurement from an odometer and error in the centripetal acceleration difference as a new observable from SINS sensors. In addition, an adaptive federated Kalman filter (AFKF) is designed, which integrates the magnetometer on the basis of the SINS\/OD navigation system. It is shown that the accuracy of the new method is higher than of SINS, and using it with the magnetometer in the integrated navigation system yields more accurate estimations. Finally, field tests show that the SINS\/OD\/MAG system improves the precision of the navigation system and promotes a fault-tolerant performance. The proposed approach can be used as a backup navigation system during outages of the Global Positioning System (GPS) for an extended amount of time with the navigation error noticeably bounded. The redundancy and integrity of the entire navigation system are also further enhanced.<\/p>\n\n\n\n

Keywords:\u00a0Navigation System Model, Vehicle Integrating Navigation, Kalman Filter, Fault-tolerant performance<\/em><\/p>\n\n\n\n

<\/div>\n\n\n\n
\n
    \n
  1. [1] Titterton, D., J. L. Weston, and J. Weston (2004) Strapdown Inertial Navigation Technology 17, IET.<\/span><\/li>\n
  2. [2] Cai, C. L., L. Yi, and Y. W. Liu (2009) Status quo <\/span>and trend of inertial integrated navigation system based on MEMS, Journal <\/span>of Chinese Inertial Technology 17, 562\u2013567.<\/span><\/li>\n
  3. [3] Yu, G.-M., J. Xiong, H. Guo, and J.-X. Wang (2014) <\/span>GNSS\/INS\/VKM vehicle integrated navigation system, China Satellite Navigatio<\/span>n Conference (CSNC), 2014 Proceedings: Volume III, 585\u2013594. doi: 10.1007\/ 978-3-642-54740-9_51<\/span><\/li>\n
  4. [4] Morgado, M., P. Batista, P. Oliveira, and C. Silvestre (2011) Po<\/span>sition USBL\/DVL sensor-based navigation filter in the presenc<\/span>e of unknown ocean currents, Automatica 47(12), 2604\u20132614. doi: 10.1016\/j.automatica. 2011.09.024<\/li>\n
  5. [5] Zhou, B., and X. Cheng (2010) Federated filtering algorithm based on fuzzy adaptive UKF for marine <\/span>SINS\/GPS\/DVL integrated system, Chinese Control and Decision Conference, 2082\u20132085. doi: 10.1109\/ CCDC.2010.549886<\/span>9<\/span><\/li>\n
  6. [6] <\/span>Peng, D., and X. Nie (2009) <\/span>The low cost MINS\/GPS integrated navigation system\u2019s design and application, Chinese Jour<\/span>nal of Sensors & Actuators.<\/span><\/li>\n
  7. [7] Li, X., and Q. Xu (2016) A reliable fusion positioning strategy for land <\/span>vehicles in GPS-denied environments based<\/span> on low-cost sensors, IEEE Transactions on Industrial Electronics PP, 1\u20131.<\/span><\/li>\n
  8. [8] Wang, M., and Y. Fu (2009) Data fusion of ALV GPS\/ DR integrated navigation system <\/span>based on BP neural network, IEEE Internat<\/span>ional Conference on Industrial Technology, 1\u20134. doi: 10.1109\/ICIT.2009.4939595<\/span><\/li>\n
  9. [9] Cai, C. L., Y. Liu, and Y. W. Liu (2009) Status quo <\/span>and trend of inertial integrated navigation system based on MEMS, Jou<\/span>rnal of Chinese Inertial Technology 17, 562\u2013567.<\/span><\/li>\n
  10. [10] Liu, H., Z. Wang, S. Fang, and C. Li (2017) MEMS based SINS\/<\/span>OD filter for land vehicles\u2019 applications, Mathematical Problems <\/span>in Engineering 2017, 1\u20139. doi: 10.1155\/2017\/1691320<\/span><\/li>\n
  11. [<\/span>11] Castagnetti, C., L. Biagi, and A. Capra (2011) Design of a low-cost GPS\/magnetometer system for land-based navigation: <\/span>integration and autocalibration algorithms, In FIG Working Week 2011-Bridging the Gap between Cultures, 1\u201315.<\/span><\/li>\n
  12. [<\/span>12<\/span>] Thompson, M. J., M. Li, and D. A. Horsley (2011) Low power 3-axis Lorentz force navigation magnetometer, <\/span>IEEE International C<\/span>onference on MICRO Electro Mechanical Systems, 593\u2013596. doi: 10.1109\/ MEMSYS.2011.5734494<\/span><\/li>\n
  13. [1<\/span>3] Liu, C. S. (2012) A globally optimal <\/span>iterative algorithm to solve an ill-posed linear system, Computer Modeling in <\/span>Engineering & Sciences 84, 383\u2013403.<\/span><\/li>\n
  14. [14] Bonnabel, S., P. Martin, and <\/span>E. Salaun (2009) Invariant extended Kalman filter: theory and application to a velocity-aided<\/span> attitude estimation problem, Decision and Control, 2009 <\/span>Held Jointly with the 2009 Chinese Control Conference. Cdc\/cc<\/span>c 2009. Proceedings of the <\/span>IEEE Conference on, 1297\u20131304.<\/span><\/li>\n
  15. [15] Hemerly, E. M., and V. R. Schad (2005) Real-time implementation of a <\/span>low cost INS\/GPS Kalman filter based navigation sys<\/span>tem, International Congress of Mechanical Engineering, Ouro Preto.<\/span><\/li>\n
  16. [16] Bo-Wen, L. I., D. Y. Yao, D. O. Automation, and T. University (<\/span>2014) Low-cost MEMS IMU navigation positioning method for lan<\/span>d vehicle, Journal of Chinese Inertial Technology.<\/span><\/li>\n
  17. [17] Wu, Y., C. Goodall, and N. El-Sheimy (2010) Self-calibration for IMU\/odometer land navigation: <\/span>simulation and test <\/span>results, In Proceedings of the ION International Technical Meeting, San Diego, CA, USA, 329\u2013334.<\/span><\/li>\n
  18. [18] Nassar, S., and N. El-Sheimy (2006) A combined algorithm of improving INS <\/span>error modeling and sensor measurements for accura<\/span>te INS\/GPS navigation, Gps Solutions 10(1), 29\u201339. doi: 10.1007\/s10291-005-0149-3<\/span><\/li>\n
  19. [19] Dah-Jing, J. and T. P. Weng (2008) An adaptive sensor fusion method with applications in integrated <\/span>navigation, Journal of Navigation 61(4), 705\u2013721. doi: 10.1017\/S0373463308004827<\/li>\n
  20. [20] Loebis, D., R. Sutton, J. Chudley, and W. Naeem (2004) Adaptive tuning of a Kalman filter via fuzzy logic for an intelligent AUV navigation system, Control Engineering Practice 12(12), 1531\u20131539. doi: 10.1016\/j.conengprac.2003.11.008<\/span><\/li>\n
  21. [<\/span>21] Sokolovic, V. S., G. Dikic, and R. Stancic (2013) Integration of INS, GPS, magnetometer and barometer for improving accuracy<\/span> navigation of the vehicle, Defence Science Journal 63, 451\u2013455. doi: 10.14429\/dsj.63. 4534<\/span><\/li>\n
  22. [2<\/span>2] Coco, S., G. Chisari, P. D. Falco, E. Iraci, S. Militello, and A. Laudani (2014) Accurate estimation of vehicle attitude for satellite tracking in Ka Band SOTM, European Modelling Symposium, 409\u2013414. doi: 10.1109\/ EMS.2014.57<\/li>\n<\/ol>\n<\/div>\n\n\n\n

    <\/p>\n","protected":false},"author":3,"template":"wp-custom-template-detail-4-aricles","meta":{"_uag_custom_page_level_css":""},"categories":[1284,6,1286],"tags":[1317],"acf":[],"uagb_featured_image_src":[],"uagb_author_info":{"display_name":"\u6797\u923a\u6db5","author_link":"\/jase\/?author=3"},"uagb_comment_info":0,"uagb_excerpt":" Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited. Download Citation:  BibTeX | http:\/\/dx.doi.org\/10.6180\/jase.201906_22(2).0009   Download PDF This paper details a new model for land vehicle navigation including…","_links":{"self":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/tkuisotope\/6539"}],"collection":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/tkuisotope"}],"about":[{"href":"\/jase\/index.php?rest_route=\/wp\/v2\/types\/tkuisotope"}],"author":[{"embeddable":true,"href":"\/jase\/index.php?rest_route=\/wp\/v2\/users\/3"}],"wp:attachment":[{"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6539"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6539"},{"taxonomy":"post_tag","embeddable":true,"href":"\/jase\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6539"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}