{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T14:30:42Z","timestamp":1762353042176,"version":"build-2065373602"},"reference-count":21,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,4,18]],"date-time":"2021-04-18T00:00:00Z","timestamp":1618704000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In this article, a smart pedestrian navigation system is developed to be implemented in a common smartphone. The main phases that characterize a pedestrian navigation system that is based on dead reckoning are introduced. A suitable Phase-Locked Loop is designed and the algorithm to estimate the direction of the user\u2019s motion between one step and the next is developed. Finally, a suitable multi-rate Kalman filter (KF) is considered to merge the information from the pedestrian dead reckoning (PDR) navigation with the data provided by the global navigation satellite systems (GNSS). The proposed GNSS\/PDR navigation system is implemented in Simulink as a finite-state machine and allows to define a trade-off between energy-saving and performance improvement in terms of position accuracy. The presented pedestrian navigation system is independent of the body-worn location of the smartphone and implements a compensation strategy of the systematic errors that are committed on the step-length estimation and the determination of the motion direction. Moreover, several tests are performed by walking in urban and suburban environments: the results show that a suitable trade-off between energy-saving and position accuracy can be reached by switching the GNSS receiver on and off.<\/jats:p>","DOI":"10.3390\/rs13081567","type":"journal-article","created":{"date-parts":[[2021,4,19]],"date-time":"2021-04-19T06:35:53Z","timestamp":1618814153000},"page":"1567","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["A Real-Time GNSS\/PDR Navigation System for Mobile Devices"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1526-7715","authenticated-orcid":false,"given":"Michele","family":"Basso","sequence":"first","affiliation":[{"name":"Department of Information Engineering, University of Florence, via di Santa Marta 3, 50139 Florence, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8509-5322","authenticated-orcid":false,"given":"Alessio","family":"Martinelli","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Florence, via di Santa Marta 3, 50139 Florence, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0145-8406","authenticated-orcid":false,"given":"Simone","family":"Morosi","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Florence, via di Santa Marta 3, 50139 Florence, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2796-1501","authenticated-orcid":false,"given":"Fabrizio","family":"Sera","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Florence, via di Santa Marta 3, 50139 Florence, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.measurement.2015.04.017","article-title":"Health parameters monitoring by smartphone for quality of life improvement","volume":"73","author":"Lamonaca","year":"2015","journal-title":"Measurement"},{"key":"ref_2","unstructured":"Groves, P. (2013). Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems, Artech House."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Angrisano, A., Vultaggio, M., Gaglione, S., and Crocetto, N. (2019, January 9\u201312). Pedestrian localization with PDR supplemented by GNSS. Proceedings of the European Navigation Conference (ENC), Warsaw, Poland.","DOI":"10.1109\/EURONAV.2019.8714150"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Giarr\u00e9, L., Pascucci, F., Morosi, S., and Martinelli, A. (2018, January 10\u201313). Improved PDR localization via UWB-anchor based on-line calibration. Proceedings of the 4th International Forum on Research and Technology for Society and Industry (RTSI), Palermo, Italy.","DOI":"10.1109\/RTSI.2018.8548377"},{"key":"ref_5","unstructured":"Sensortec, B. (2021, March 11). BMI160-Data sheet. Prod. Specif., Available online: https:\/\/www.mouser.com\/datasheet\/2\/783\/BST-BMI160-DS000-1509569.pdf."},{"key":"ref_6","unstructured":"Asahi Kasei Microdevices Corporation (2017). AK09918 3-axis Electronic Compass. Prod. Specif, Available online: https:\/\/www.akm.com\/cn\/en\/products\/electronic-compass\/."},{"key":"ref_7","unstructured":"Hegarty, C.J., and Kaplan, E.D. (2017). Understanding GPS\/GNSS: Principles and Applications, Artech House."},{"key":"ref_8","unstructured":"van Diggelen, F. (2009). A-GPS: Assisted GPS, GNSS, and SBAS, Artech House."},{"key":"ref_9","unstructured":"Veness, C. Calculate distance, bearing and more between Latitude\/Longitude points. Movable Type Scripts, Available online: https:\/\/www.movable-type.co.uk\/scripts\/latlong.html."},{"key":"ref_10","first-page":"113","article-title":"An efficient orientation filter for inertial and inertial\/magnetic sensor arrays","volume":"25","author":"Madgwick","year":"2010","journal-title":"Rep. x-io Univ. Bristol (UK)"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2499","DOI":"10.1007\/s11277-020-07338-7","article-title":"Smart Phone Based Sensor Fusion by Using Madgwick Filter for 3D Indoor Navigation","volume":"113","author":"Hasan","year":"2020","journal-title":"Wirel. Pers. Commun."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"174","DOI":"10.17706\/IJCEE.2018.10.3.174-186","article-title":"Design of a Modified Madgwick Filter for Quaternion-Based Orientation Estimation Using AHRS","volume":"10","author":"Abadir","year":"2018","journal-title":"Int. J. Comput. Electr. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1109\/JSEN.2016.2631629","article-title":"Pedestrian dead reckoning based on frequency self-synchronization and body kinematics","volume":"17","author":"Basso","year":"2016","journal-title":"IEEE Sens. J."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1600","DOI":"10.1109\/JSEN.2017.2776100","article-title":"Probabilistic context-aware step length estimation for pedestrian dead reckoning","volume":"18","author":"Martinelli","year":"2017","journal-title":"IEEE Sens. J."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Martinelli, A., Morosi, S., and Del Re, E. (2015, January 13\u201316). Daily movement recognition for dead reckoning applications. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Banff, AB, Canada.","DOI":"10.1109\/IPIN.2015.7346769"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"8507","DOI":"10.3390\/s120708507","article-title":"Step length estimation using handheld inertial sensors","volume":"12","author":"Renaudin","year":"2012","journal-title":"Sensors"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"7447","DOI":"10.1109\/JSEN.2020.2979335","article-title":"Triggered INS\/GNSS Data Fusion Algorithms for Enhanced Pedestrian Navigation System","volume":"20","author":"Basso","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Jin, Y., Toh, H.S., Soh, W.S., and Wong, W.C. (2011, January 21\u201325). A robust dead-reckoning pedestrian tracking system with low cost sensors. Proceedings of the 2011 IEEE International Conference on Pervasive Computing and Communications (PerCom), Seattle, WA, USA.","DOI":"10.1109\/PERCOM.2011.5767590"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1109\/TIM.2002.807986","article-title":"A method for dead reckoning parameter correction in pedestrian navigation system","volume":"52","author":"Jirawimut","year":"2003","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Shin, S., Park, C., Kim, J., Hong, H., and Lee, J. (2007, January 6\u20138). Adaptive step length estimation algorithm using low-cost MEMS inertial sensors. Proceedings of the 2007 IEEE Sensors Applications Symposium, San Diego, CA, USA.","DOI":"10.1109\/SAS.2007.374406"},{"key":"ref_21","unstructured":"Armesto, L., Chroust, S., Vincze, M., and Tornero, J. (May, January 26). Multi-rate fusion with vision and inertial sensors. Proceedings of the IEEE International Conference on Robotics and Automation, ICRA\u201904, New Orleans, LA, USA."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/8\/1567\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:49:21Z","timestamp":1760161761000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/8\/1567"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,18]]},"references-count":21,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2021,4]]}},"alternative-id":["rs13081567"],"URL":"https:\/\/doi.org\/10.3390\/rs13081567","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,4,18]]}}}