{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T20:36:39Z","timestamp":1769200599935,"version":"3.49.0"},"reference-count":42,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2016,5,17]],"date-time":"2016-05-17T00:00:00Z","timestamp":1463443200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The demand for pedestrian navigation has increased along with the rapid progress in mobile and wearable devices. This study develops an accurate and usable Step Length Estimation (SLE) method for a Pedestrian Dead Reckoning (PDR) system with features including a wide range of step lengths, a self-contained system, and real-time computing, based on the multi-sensor fusion and Fuzzy Logic (FL) algorithms. The wide-range SLE developed in this study was achieved by using a knowledge-based method to model the walking patterns of the user. The input variables of the FL are step strength and frequency, and the output is the estimated step length. Moreover, a waist-mounted sensor module has been developed using low-cost inertial sensors. Since low-cost sensors suffer from various errors, a calibration procedure has been utilized to improve accuracy. The proposed PDR scheme in this study demonstrates its ability to be implemented on waist-mounted devices in real time and is suitable for the indoor and outdoor environments considered in this study without the need for map information or any pre-installed infrastructure. The experiment results show that the maximum distance error was within 1.2% of 116.51 m in an indoor environment and was 1.78% of 385.2 m in an outdoor environment.<\/jats:p>","DOI":"10.3390\/ijgi5050070","type":"journal-article","created":{"date-parts":[[2016,5,17]],"date-time":"2016-05-17T10:20:11Z","timestamp":1463480411000},"page":"70","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A Knowledge-Based Step Length Estimation Method Based on Fuzzy Logic and Multi-Sensor Fusion Algorithms for a Pedestrian Dead Reckoning System"],"prefix":"10.3390","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3471-3290","authenticated-orcid":false,"given":"Ying-Chih","family":"Lai","sequence":"first","affiliation":[{"name":"Department of Aerospace and Systems Engineering, Feng Chia University, No. 100, Wenhwa Road, Seatwen District, Taichung 407, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chin-Chia","family":"Chang","sequence":"additional","affiliation":[{"name":"Industrial Technology Research Institute, No. 195, Sec. 4, Chung Hsing Rd., Chutung, Hsinchu 310, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chia-Ming","family":"Tsai","sequence":"additional","affiliation":[{"name":"Industrial Technology Research Institute, No. 195, Sec. 4, Chung Hsing Rd., Chutung, Hsinchu 310, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shih-Ching","family":"Huang","sequence":"additional","affiliation":[{"name":"Industrial Technology Research Institute, No. 195, Sec. 4, Chung Hsing Rd., Chutung, Hsinchu 310, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai-Wei","family":"Chiang","sequence":"additional","affiliation":[{"name":"Department of Geomatics Engineering, National Cheng-Kung University, No. 1, Daxue Road, East District, Tainan 701, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,5,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1109\/TITB.2007.899496","article-title":"Detection of daily activities and sports with wearable sensors in controlled and uncontrolled conditions","volume":"12","author":"Ermes","year":"2008","journal-title":"IEEE Trans. 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