{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:47:47Z","timestamp":1760402867955,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,4,30]],"date-time":"2020-04-30T00:00:00Z","timestamp":1588204800000},"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>Using the Global Navigation Satellite System (GNSS), it is difficult to provide continuous and reliable position service for vehicle navigation in complex urban environments, due to the natural vulnerability of the GNSS signal. With the rapid development of the sensor technology and the reduction in their costs, the positioning performance of GNSS is expected to be significantly improved by fusing multi-sensors. In order to improve the continuity and reliability of the vehicle navigation system, we proposed a multi-sensor tight fusion (MTF) method by combining the inertial navigation system (INS), odometer, and barometric altimeter with the GNSS technique. Different fusion strategies were presented in the open-sky, insufficient satellite, and satellite outage environments to check the performance improvement of the proposed method. The simulation and real-device tests demonstrate that in the open-sky context, the error of sensors can be estimated correctly. This is useful for sensor noise compensation and position accuracy improvement, when GNSS is unavailable. In the insufficient satellite context (6 min), with the help of the barometric altimeter and a clock model, the accuracy of the method can be close to that in the open-sky context. In the satellite outage context, the error divergence of the MTF is obviously slower than the traditional GNSS\/INS tightly coupled integration, as seen by odometer and barometric altimeter assisting.<\/jats:p>","DOI":"10.3390\/s20092551","type":"journal-article","created":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T14:00:43Z","timestamp":1588600843000},"page":"2551","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Multi-Sensor Tight Fusion Method Designed for Vehicle Navigation"],"prefix":"10.3390","volume":"20","author":[{"given":"Qifeng","family":"Lai","sequence":"first","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100864, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100864, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Yuan","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100864, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongyan","family":"Wei","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100864, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ningbo","family":"Wang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100864, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3911-3059","authenticated-orcid":false,"given":"Zishen","family":"Li","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100864, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinchun","family":"Ji","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100864, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez, E., David, C., and Par\u00e9s, M. (2017). CSAC Characterization and Its Impact on GNSS Clock Augmentation Performance. Sensors, 17.","DOI":"10.3390\/s17020370"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1017\/S0373463307004316","article-title":"Improving Adaptive Kalman Estimation in GPS\/INS Integration","volume":"60","author":"Ding","year":"2007","journal-title":"J. Navig."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.measurement.2017.01.053","article-title":"A hybrid fusion algorithm for GPS\/INS integration during GPS outage","volume":"103","author":"Yao","year":"2017","journal-title":"Measurement"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s10291-015-0511-z","article-title":"PPP\/INS tightly coupled navigation using adaptive federated filter","volume":"21","author":"Li","year":"2017","journal-title":"GPS Solut."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"255","DOI":"10.3390\/s17020255","article-title":"Loose and Tight GNSS\/INS Integrations: Comparison of Performance Assessed in Real Urban Scenarios","volume":"17","author":"Gianluca","year":"2017","journal-title":"Sensors"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/s10291-006-0050-8","article-title":"GPS\/MEMS INS integrated system for navigation in urban areas","volume":"11","author":"Godha","year":"2007","journal-title":"GPS Solut."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"10599","DOI":"10.3390\/s130810599","article-title":"The Performance Analysis of a Real-Time Integrated INS\/GPS Vehicle Navigation System with Abnormal GPS Measurement Elimination","volume":"13","author":"Chiang","year":"2013","journal-title":"Sensors"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"561","DOI":"10.3390\/s20020561","article-title":"Tightly Coupled GNSS\/INS Integration with Robust Sequential Kalman Filter for Accurate Vehicular Navigation","volume":"20","author":"Yi","year":"2020","journal-title":"Sensors"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Paziewski, J. (2020). Recent advances and perspectives for positioning and applications with smartphone GNSS observations. Meas. Sci. Technol., 1\u201314.","DOI":"10.1088\/1361-6501\/ab8a7d"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Walter, O., Schmalenstroeer, J., Engler, A., and Haeb-Umbach, R. (2013). Smartphone-Based Sensor Fusion for Improved Vehicular Navigation. 2013 10th Workshop on Positioning, Navigation and Communication (WPNC), IEEE.","DOI":"10.1109\/WPNC.2013.6533261"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1109\/TVT.2009.2034267","article-title":"Bayoumi, M.M. Low-Cost Three-Dimensional Navigation Solution for RISS\/GPS Integration Using Mixture Particle Filter","volume":"59","author":"Georgy","year":"2010","journal-title":"IEEE Trans. Veh. Tech."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"13101","DOI":"10.1109\/ACCESS.2018.2813000","article-title":"Positioning Based on Tightly Coupled Multiple Sensors: A Practical Implementation and Experimental Assessment","volume":"6","author":"Falco","year":"2018","journal-title":"IEEE Access"},{"key":"ref_13","first-page":"1","article-title":"Performance of Tightly Coupled Integration of GPS\/BDS\/MEMS-INS\/Odometer for Real-Time High-Precision Vehicle Positioning in Urban Degraded and Denied Environment","volume":"2020","author":"Fei","year":"2020","journal-title":"J. Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1007\/s10291-010-0186-4","article-title":"Noureldin, A. Enhanced MEMS-IMU\/odometer\/GPS integration using mixture particle filter","volume":"15","author":"Georgy","year":"2011","journal-title":"GPS Solut."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1017\/S0373463314000307","article-title":"GPS\/INS\/Odometer Integrated System Using Fuzzy Neural Network for Land Vehicle Navigation Applications","volume":"67","author":"Li","year":"2014","journal-title":"J. Navig."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Parviainen, J., Kantola, J., and Collin, J. (2008). Differential barometry in personal navigation. 2008 IEEE\/ION Position, Location & Navigation Symposium, IEEE.","DOI":"10.1109\/PLANS.2008.4570051"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1007\/s10291-015-0497-6","article-title":"Positioning with two satellites and known receiver clock, barometric pressure and radar elevation","volume":"20","author":"Yen","year":"2015","journal-title":"GPS Solut."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3057","DOI":"10.1109\/JSEN.2019.2954532","article-title":"Assessment for INS\/GNSS\/Odometer\/Barometer Integration in Loosely-Coupled and Tightly-Coupled Scheme in a GNSS-Degraded Environment","volume":"20","author":"Chiang","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_19","unstructured":"Mcburney, P.W., and Brown, R.G. (1988, January 26\u201329). Receiver clock stability\u2014An important aid in the GPS integrity problem. Proceedings of the Institute of Navigation, National Technical Meeting, Santa Barbara, CA, USA."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"754","DOI":"10.15837\/ijccc.2013.5.645","article-title":"A Quick Location Method for High Dynamic GNSS Receiver Based on Time Assistance","volume":"8","author":"Wu","year":"2013","journal-title":"Int. J. Comput. Commun. Control"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1007\/s10291-015-0480-2","article-title":"Benefits of receiver clock modeling in code-based GNSS navigation","volume":"20","author":"Krawinkel","year":"2016","journal-title":"GPS Solut."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Li, B., Zhang, H., Wang, W., and Li, X. (2019, January 14\u201318). BDS in Challenge Environment Using CSAC. Proceedings of the 2019 Joint Conference of the IEEE International Frequency Control Symposium and European Frequency and Time Forum (EFTF\/IFC), Orlando, FL, USA.","DOI":"10.1109\/FCS.2019.8856095"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Zhou, P., Zheng, Y., Li, Z., Li, M., and Shen, G. (2012, January 6\u20139). IODetector: A Generic Service for Indoor\/Outdoor Detection. Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems, Toronto, ON, Canada.","DOI":"10.1145\/2426656.2426709"},{"key":"ref_24","first-page":"18","article-title":"Toward a Unified PNT, Part 1: Complexity and context: Key challenges of multisensor positioning","volume":"25","author":"Groves","year":"2014","journal-title":"GPS World"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5742","DOI":"10.3390\/s140405742","article-title":"Context-Aware Personal Navigation Using Embedded Sensor Fusion in Smartphones","volume":"14","author":"Saeedi","year":"2014","journal-title":"Sensors"},{"key":"ref_26","unstructured":"Kaplan, E., and Hegarty, C. (2017). Understanding GPS: Principles and Applications, Artech House. [3rd ed.]."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Titterton, D., and Weston, J.L. (2004). Strapdown Inertial Navigation Technology, IET. [2nd ed.].","DOI":"10.1049\/PBRA017E"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Liu, K., Wang, Y., and Wang, J. (2014). Differential Barometric Altimetry Assists Floor Identification in WLAN Location Fingerprinting Study. Principle and Application Progress in Location-Based Services, Springer International Publishing.","DOI":"10.1007\/978-3-319-04028-8_2"},{"key":"ref_29","unstructured":"National Oceanic and Atmospheric Administration (1976). U.S. Standard Atmosphere."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/9\/2551\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T14:09:28Z","timestamp":1760364568000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/9\/2551"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,30]]},"references-count":29,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["s20092551"],"URL":"https:\/\/doi.org\/10.3390\/s20092551","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2020,4,30]]}}}