{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T06:10:29Z","timestamp":1776319829656,"version":"3.50.1"},"reference-count":35,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,3,12]],"date-time":"2020-03-12T00:00:00Z","timestamp":1583971200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In pedestrian inertial navigation, multi-sensor fusion is often used to obtain accurate heading estimates. As a widely distributed signal source, the geomagnetic field is convenient to provide sufficiently accurate heading angles. Unfortunately, there is a broad presence of artificial magnetic perturbations in indoor environments, leading to difficulties in geomagnetic correction. In this paper, by analyzing the spatial distribution model of the magnetic interference field on the geomagnetic field, two quantitative features have been found to be crucial in distinguishing normal magnetic data from anomalies. By leveraging these two features and the classification and regression tree (CART) algorithm, we trained a decision tree that is capable of extracting magnetic data from distorted measurements. Furthermore, this well-trained decision tree can be used as a reject gate in a Kalman filter. By combining the decision tree and Kalman filter, a high-precision indoor pedestrian navigation system based on a magnetically assisted inertial system is proposed. This system is then validated in a real indoor environment, and the results show that our system delivers state-of-the-art positioning performance. Compared to other baseline algorithms, an improvement of over 70% in the positioning accuracy is achieved.<\/jats:p>","DOI":"10.3390\/s20061578","type":"journal-article","created":{"date-parts":[[2020,3,12]],"date-time":"2020-03-12T12:22:51Z","timestamp":1584015771000},"page":"1578","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Improving the Heading Accuracy in Indoor Pedestrian Navigation Based on a Decision Tree and Kalman Filter"],"prefix":"10.3390","volume":"20","author":[{"given":"Guanghui","family":"Hu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China"},{"name":"School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China;"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weizhi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Vtran Tech (Chang Zhou) CO., Ltd., Shanghai 200135, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Wan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China"},{"name":"Vtran Tech (Chang Zhou) CO., Ltd., Shanghai 200135, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinxin","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China"},{"name":"School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China;"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,12]]},"reference":[{"key":"ref_1","first-page":"10","article-title":"3D Reconstruction of Pedestrian Trajectory with Moving Direction Learning and Optimal Gait Recognition","volume":"2018","author":"Wang","year":"2018","journal-title":"Complexity"},{"key":"ref_2","unstructured":"Ali, A., Al-Hamad, A., Georgy, J., Chang, H.W., and Inst, N. (2015). Portable Device Use Case Recognition Technique for Pedestrian Navigation. Proceedings of the 28th International Technical Meeting of the Satellite Division of the Institute of Navigation, Institute of Navigation."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1007\/s11265-013-0865-9","article-title":"Indoor Localization Methods Using Dead Reckoning and 3D Map Matching","volume":"76","author":"Bojja","year":"2014","journal-title":"J. Signal Process. Syst. Signal Image Video Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"6509","DOI":"10.1007\/s11277-017-4852-5","article-title":"Advanced Indoor Positioning Using Zigbee Wireless Technology","volume":"97","author":"Uradzinski","year":"2017","journal-title":"Wirel. Pers. Commun."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3322241","article-title":"Indoor Localization Improved by Spatial Context - A Survey","volume":"52","author":"Gu","year":"2019","journal-title":"Acm Comput. Surv."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1281","DOI":"10.1109\/SURV.2012.121912.00075","article-title":"A Survey of Indoor Inertial Positioning Systems for Pedestrians","volume":"15","author":"Harle","year":"2013","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Ebner, F., Fetzer, T., Deinzer, F., and Grzegorzek, M. (2017). On Wi-Fi Model Optimizations for Smartphone-Based Indoor Localization. Isprs Int. Geo-Inf., 6.","DOI":"10.3390\/ijgi6080233"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3626","DOI":"10.1109\/TWC.2006.256985","article-title":"RSS-Based Location Estimation with Unknown Pathloss Model","volume":"5","author":"Li","year":"2006","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Jacq, D., Chatonnay, P., Bloch, C., Canalda, P., and Spies, F. (2017, January 18\u201321). Towards zero-configuration for Wi-Fi indoor positioning system. Proceedings of the 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Sapporo, Japan.","DOI":"10.1109\/IPIN.2017.8115951"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Meng, W., Xiao, W., Ni, W., and Xie, L. (2011, January 21\u201323). Secure and robust Wi-Fi fingerprinting indoor localization. Proceedings of the 2011 International Conference on Indoor Positioning and Indoor Navigation, Guimaraes, Portugal.","DOI":"10.1109\/IPIN.2011.6071908"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Correa, A., Diaz, E.M., Ahmed, D.B., Morell, A., and Vicario, J.L. (2016). Advanced Pedestrian Positioning System to Smartphones and Smartwatches. Sensors, 16.","DOI":"10.3390\/s16111903"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Chen, J., Glover, M., Yang, C., Li, C., Li, Z., and Cangelosi, A. (2017, January 19\u201321). Development of an Immersive Interface for Robot Teleoperation. Proceedings of the Annual Conference towards Autonomous Robotic Systems, Guildford, UK.","DOI":"10.1007\/978-3-319-64107-2_1"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Lu, C., Uchiyama, H., Thomas, D., Shimada, A., and Taniguchi, R.-i. (2019). Indoor Positioning System Based on Chest-Mounted IMU. Sensors, 19.","DOI":"10.3390\/s19020420"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Tian, Z.S., Zhang, Y., Zhou, M., and Liu, Y. (2014). Pedestrian dead reckoning for MARG navigation using a smartphone. Eurasip J. Adv. Signal Process., 65.","DOI":"10.1186\/1687-6180-2014-65"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Khedr, M., and El-Sheimy, N. (2017). A Smartphone Step Counter Using IMU and Magnetometer for Navigation and Health Monitoring Applications. Sensors, 17.","DOI":"10.3390\/s17112573"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1109\/MCG.2005.140","article-title":"Pedestrian tracking with shoe-mounted inertial sensors","volume":"25","author":"Foxlin","year":"2005","journal-title":"IEEE Comput. Graph. Appl."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Tjhai, C., and Keefe, K.O. (2018, January 24\u201327). Comparing Heading Estimates from Multiple Wearable Inertial and Magnetic Sensors Mounted on Lower Limbs. Proceedings of the 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nantes, France.","DOI":"10.1109\/IPIN.2018.8533740"},{"key":"ref_18","unstructured":"Afzal, M.H., Renaudin, V., and Lachapelle, G. (2010, January 21\u201324). Assessment of Indoor Magnetic Field Anomalies using Multiple Magnetometers. Proceedings of the 23rd International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS 2010), Portland, OR, USA."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Song, J.W., and Park, C.G. (2018). Enhanced Pedestrian Navigation Based on Course Angle Error Estimation Using Cascaded Kalman Filters. Sensors, 18.","DOI":"10.3390\/s18041281"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"11390","DOI":"10.3390\/s111211390","article-title":"Use of Earth\u2019s Magnetic Field for Mitigating Gyroscope Errors Regardless of Magnetic Perturbation","volume":"11","author":"Afzal","year":"2011","journal-title":"Sensors"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Bancroft, J.B., and Lachapelle, G. (2012, January 23\u201326). Use of Magnetic Quasi Static Field (QSF) Updates for Pedestrian Navigation. Proceedings of the 2012 IEEE\/Ion Position Location and Navigation Symposium, Myrtle Beach, SC, USA.","DOI":"10.1109\/PLANS.2012.6236934"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhang, W., Wei, D., Gong, P., and Yuan, H. (2018). The PDR System Based on Improved QSF+ Map Matching Algorithm. China Satellite Navigation Conference (CSNC) 2018 Proceedings, Springer.","DOI":"10.1007\/978-981-13-0029-5_63"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"12618","DOI":"10.1016\/j.eswa.2012.05.021","article-title":"Technology trends analysis and forecasting application based on decision tree and statistical feature analysis","volume":"39","author":"Kim","year":"2012","journal-title":"Expert Syst. Appl."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Li, C., Yang, C., Wan, J., Annamalai, A., and Cangelosi, A. (2017, January 7\u20138). Neural learning and Kalman filtering enhanced teaching by demonstration for a Baxter robot. Proceedings of the 2017 23rd International Conference on Automation and Computing (ICAC), Huddersfield, UK.","DOI":"10.23919\/IConAC.2017.8081985"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1109\/TSMCC.2004.843247","article-title":"Top-down induction of decision trees classifiers\u2014A survey","volume":"35","author":"Rokach","year":"2005","journal-title":"IEEE Trans. Syst. Manand Cybern. Part C (Appl. Rev.)"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Chiang, K.W., Liao, J.K., Tsai, G.J., and Chang, H.W. (2016). The Performance Analysis of the Map-Aided Fuzzy Decision Tree Based on the Pedestrian Dead Reckoning Algorithm in an Indoor Environment. Sensors, 16.","DOI":"10.3390\/s16010034"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Deng, Z.A., Wang, G.F., Hu, Y., and Cui, Y. (2016). Carrying Position Independent User Heading Estimation for Indoor Pedestrian Navigation with Smartphones. Sensors, 16.","DOI":"10.3390\/s16050677"},{"key":"ref_28","unstructured":"(2019, October 12). The World Magnetic Model, Available online: https:\/\/www.ngdc.noaa.gov\/geomag\/WMM\/."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Klipp, K., Ros\u00e9, H., Willaredt, J., Sawade, O., and Radusch, I. (2018, January 24\u201327). Rotation-Invariant Magnetic Features for Inertial Indoor-Localization. Proceedings of the 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nantes, France.","DOI":"10.1109\/IPIN.2018.8533842"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1155\/2010\/967245","article-title":"Complete Triaxis Magnetometer Calibration in the Magnetic Domain","volume":"2010","author":"Renaudin","year":"2010","journal-title":"J. Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1109\/TIM.2013.2281562","article-title":"Calibration of Miniature Inertial and Magnetic Sensor Units for Robust Attitude Estimation","volume":"63","author":"Zhang","year":"2014","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_32","unstructured":"Afzal, M.H. (2011). Use of Earth\u2019s Magnetic Field for Pedestrian Navigation. [Ph.D Thesis, University of Calgary]."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Jaehyun, P., Yunki, K., and Jangmyung, L. (2012, January 26\u201328). Waist mounted Pedestrian Dead-Reckoning system. Proceedings of the 2012 9th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Daejeon, Korea.","DOI":"10.1109\/URAI.2012.6463008"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Diaz, E.M., and Gonzalez, A.L.M. (2014). Step Detector and Step Length Estimator for an Inertial Pocket Navigation System. 2014 International Conference on Indoor Positioning and Indoor Navigation, IEEE.","DOI":"10.1109\/IPIN.2014.7275473"},{"key":"ref_35","first-page":"1","article-title":"Using the ADXL202 in Pedometer and Personal Navigation Applications","volume":"2","author":"Weinberg","year":"2002","journal-title":"Analog Devices -602 Appl. 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