a232cb625aaa37701aeab29d9c50e92a sensors_a2016v16n11p1903.pdf d9970aff5d395d697c33acc9f64ab51bb178fb61 sensors_a2016v16n11p1903.pdf 73d85667f5f60cb63bd4aafe2ae06a7d33456fda44aa278ec7f3c214b9301fdd sensors_a2016v16n11p1903.pdf Title: Advanced Pedestrian Positioning System to Smartphones and Smartwatches Subject: In recent years, there has been an increasing interest in the development of pedestrian navigation systems for satellite-denied scenarios. The popularization of smartphones and smartwatches is an interesting opportunity for reducing the infrastructure cost of the positioning systems. Nowadays, smartphones include inertial sensors that can be used in pedestrian dead-reckoning (PDR) algorithms for the estimation of the user's position. Both smartphones and smartwatches include WiFi capabilities allowing the computation of the received signal strength (RSS). We develop a new method for the combination of RSS measurements from two different receivers using a Gaussian mixture model. We also analyze the implication of using a WiFi network designed for communication purposes in an indoor positioning system when the designer cannot control the network configuration. In this work, we design a hybrid positioning system that combines inertial measurements, from low-cost inertial sensors embedded in a smartphone, with RSS measurements through an extended Kalman filter. The system has been validated in a real scenario, and results show that our system improves the positioning accuracy of the PDR system thanks to the use of two WiFi receivers. The designed system obtains an accuracy up to 1.4 m in a scenario of 6000 m2. Keywords: inertial sensors and systems; smartphone navigation systems; aiding technology for INS; smartwatch; received signal strength Author: Alejandro Correa, Estefania Munoz Diaz, Dina Bousdar Ahmed, Antoni Morell and Jose Lopez Vicario Creator: LaTeX with hyperref package Producer: pdfTeX-1.40.15 CreationDate: Fri Nov 11 16:55:19 2016 ModDate: Fri Nov 11 16:55:19 2016 Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 18 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 2593125 bytes Optimized: no PDF version: 1.5 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- ZIFJVZ+URWPalladioL-Ital Type 1 Custom yes yes no 67 0 DMGJMH+URWPalladioL-Bold Type 1 Custom yes yes no 68 0 YIISCU+URWPalladioL-Roma Type 1 Custom yes yes no 69 0 RVSEMT+TimesNewRomanPS-BoldItalicMT Type 1C WinAnsi yes yes no 73 0 MWRFWX+CMR10 Type 1 Builtin yes yes no 156 0 YTMALV+CMEX10 Type 1 Builtin yes yes no 157 0 LAHFAN+CMSY10 Type 1 Builtin yes yes no 159 0 LPFURB+PazoMath-Italic Type 1 Builtin yes yes no 174 0 MWRFWX+CMR10 Type 1 Custom yes yes no 181 0 MWRFWX+CMR10 Type 1 Custom yes yes no 183 0 MWRFWX+CMR10 Type 1 Custom yes yes no 185 0 MWRFWX+CMR10 Type 1 Custom yes yes no 187 0 MWRFWX+CMR10 Type 1 Custom yes yes no 189 0 MWRFWX+CMR10 Type 1 Custom yes yes no 191 0 MWRFWX+CMR10 Type 1 Custom yes yes no 193 0 MWRFWX+CMR10 Type 1 Custom yes yes no 195 0 MWRFWX+CMR10 Type 1 Custom yes yes no 197 0 FFOIXN+CMR9 Type 1 Custom yes yes no 204 0 TEXRGU+CMTI10 Type 1 Custom yes yes no 207 0 GWJHDA+CMMI9 Type 1 Custom yes yes no 210 0 MWRFWX+CMR10 Type 1 Custom yes yes no 212 0 UBNINU+PazoMath Type 1 Builtin yes yes no 234 0 XFBPDX+Cambria-Identity-H CID Type 0C Identity-H yes yes no 250 0 IKVETA+mwb.cmmi10 Type 1C Custom yes yes no 251 0 GIFLKZ+ArialMT TrueType WinAnsi yes yes yes 252 0 ZWCLCS+Times-Roman Type 1C WinAnsi yes yes no 289 0 BGZNNT+Times-Roman-Bold Type 1C WinAnsi yes yes no 290 0 ZWCLCS+Times-Roman Type 1C WinAnsi yes yes no 297 0 HNKKSN+Times-Roman-Bold Type 1C WinAnsi yes yes no 298 0 OOERYY+Times-Roman Type 1C WinAnsi yes yes no 421 0 WLOOCB+Times-Roman-Bold Type 1C WinAnsi yes yes no 422 0 OOERYY+Times-Roman Type 1C WinAnsi yes yes no 429 0 WLOOCB+Times-Roman-Bold Type 1C WinAnsi yes yes no 430 0 OOERYY+Times-Roman Type 1C WinAnsi yes yes no 437 0 WLOOCB+Times-Roman-Bold Type 1C WinAnsi yes yes no 438 0 WEIJUK+CMSY9 Type 1 Builtin yes yes no 462 0 java.lang.ClassCastException: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject cannot be cast to edu.harvard.hul.ois.jhove.module.pdf.PdfDictionary at edu.harvard.hul.ois.jhove.module.PdfModule.readDocCatalogDict(PdfModule.java:1284) at edu.harvard.hul.ois.jhove.module.PdfModule.parse(PdfModule.java:525) at edu.harvard.hul.ois.jhove.JhoveBase.processFile(JhoveBase.java:825) at edu.harvard.hul.ois.jhove.JhoveBase.process(JhoveBase.java:614) at edu.harvard.hul.ois.jhove.JhoveBase.dispatch(JhoveBase.java:465) at Jhove.main(Jhove.java:296) Jhove (Rel. 1.6, 2011-01-04) Date: 2017-03-29 11:28:24 CEST RepresentationInformation: sensors_a2016v16n11p1903.pdf ReportingModule: BYTESTREAM, Rel. 1.3 (2007-04-10) LastModified: 2016-12-02 12:49:54 CET Size: 2593125 Format: bytestream Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/octet-stream Checksum: 51c3f8ca Type: CRC32 Checksum: a232cb625aaa37701aeab29d9c50e92a Type: MD5 Checksum: d9970aff5d395d697c33acc9f64ab51bb178fb61 Type: SHA-1