{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T06:10:13Z","timestamp":1770963013767,"version":"3.50.1"},"reference-count":55,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,3,3]],"date-time":"2023-03-03T00:00:00Z","timestamp":1677801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shenzhen key technology research project: Key Technology Research and Development of High-Speed and High-Precision Vertical Five-Axis Machining Center","award":["2019N048"],"award-info":[{"award-number":["2019N048"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Pedestrian dead reckoning (PDR) is the critical component in indoor pedestrian tracking and navigation services. While most of the recent PDR solutions exploit in-built inertial sensors in smartphones for next step estimation, due to measurement errors and sensing drift, the accuracy of walking direction, step detection, and step length estimation cannot be guaranteed, leading to large accumulative tracking errors. In this paper, we propose a radar-assisted PDR scheme, called RadarPDR, which integrates a frequency-modulation continuous-wave (FMCW) radar to assist the inertial sensors-based PDR. We first establish a segmented wall distance calibration model to deal with the radar ranging noise caused by irregular indoor building layouts and fuse wall distance estimation with acceleration and azimuth signals measured by the inertial sensors of a smartphone. We also propose a hierarchical particle filter(PF) together with an extended Kalman filter for position and trajectory adjustment. Experiments have been conducted in practical indoor scenarios. Results demonstrate that the proposed RadarPDR is efficient and stable and outperforms the widely used inertial sensors-based PDR scheme.<\/jats:p>","DOI":"10.3390\/s23052782","type":"journal-article","created":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T02:28:34Z","timestamp":1678069714000},"page":"2782","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["RadarPDR: Radar-Assisted Indoor Pedestrian Dead Reckoning"],"prefix":"10.3390","volume":"23","author":[{"given":"Jianbiao","family":"He","sequence":"first","affiliation":[{"name":"Shenzhen Polytechnic (SZPT), Liuxian Avenue 7098, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Xiang","sequence":"additional","affiliation":[{"name":"School of Electronic Information and Communications, Huazhong University of Science and Technology (HUST), Luoyu Road 1037, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Hubei International Trade Supply Chain Management Co., Ltd., Wuhan 430000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0312-4805","authenticated-orcid":false,"given":"Bang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electronic Information and Communications, Huazhong University of Science and Technology (HUST), Luoyu Road 1037, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1347","DOI":"10.1109\/COMST.2016.2637663","article-title":"A survey of selected indoor positioning methods for smartphones","volume":"19","author":"Davidson","year":"2016","journal-title":"IEEE Commun. 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