{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T16:22:46Z","timestamp":1777652566441,"version":"3.51.4"},"reference-count":37,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2015,6,23]],"date-time":"2015-06-23T00:00:00Z","timestamp":1435017600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Micromachines"],"abstract":"<jats:p>Providing an accurate and practical navigation solution anywhere with portable devices, such as smartphones, is still a challenge, especially in environments where  global navigation satellite systems (GNSS) signals are not available or are degraded. This paper proposes a new algorithm that integrates inertial navigation system (INS) and pedestrian dead reckoning (PDR) to combine the advantages of both mechanizations for micro-electro-mechanical systems (MEMS) sensors in pedestrian navigation applications. In this PDR\/INS integration algorithm, a pseudo-velocity-vector, which is composed of the PDR-derived forward speed and zero lateral and vertical speeds from non-holonomic constraints (NHC), works as an update for the INS to limit the velocity errors. To further limit the drift of MEMS inertial sensors, trilateration-based WiFi positions with small variances are also selected as updates for the PDR\/INS integrated system. The experiments illustrate that positioning error is decreased by 60%\u201375% by using the proposed PDR\/INS integrated MEMS solution when compared with PDR. The positioning error is further decreased by 15%\u201355% if the proposed PDR\/INS\/WiFi integrated solution is implemented. The average accuracy of the proposed PDR\/INS\/WiFi integration algorithm achieves 4.5 m in indoor environments.<\/jats:p>","DOI":"10.3390\/mi6060793","type":"journal-article","created":{"date-parts":[[2015,6,23]],"date-time":"2015-06-23T10:19:06Z","timestamp":1435054746000},"page":"793-812","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":104,"title":["PDR\/INS\/WiFi Integration Based on Handheld Devices for Indoor Pedestrian Navigation"],"prefix":"10.3390","volume":"6","author":[{"given":"Yuan","family":"Zhuang","sequence":"first","affiliation":[{"name":"Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiyu","family":"Lan","sequence":"additional","affiliation":[{"name":"Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"You","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada"},{"name":"GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Naser","family":"El-Sheimy","sequence":"additional","affiliation":[{"name":"Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,6,23]]},"reference":[{"key":"ref_1","unstructured":"Kaplan, E.D., and Hegarty, C.J. 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