{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T06:26:06Z","timestamp":1742970366937,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030854614"},{"type":"electronic","value":"9783030854621"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-85462-1_16","type":"book-chapter","created":{"date-parts":[[2021,8,14]],"date-time":"2021-08-14T06:02:59Z","timestamp":1628920979000},"page":"174-185","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Wavelet Threshold Denoising and Pseudo-range Difference-Based Weighting for Indoor BLE Positioning"],"prefix":"10.1007","author":[{"given":"Yang","family":"Dai","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianqiang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,8,15]]},"reference":[{"key":"16_CR1","doi-asserted-by":"publisher","first-page":"14589","DOI":"10.1109\/ACCESS.2017.2726088","volume":"5","author":"X Wu","year":"2017","unstructured":"Wu, X., Shen, R., Fu, L., et al.: iBILL: using iBeacon and inertial sensors for accurate indoor localization in large open areas. IEEE Access 5, 14589\u201314599 (2017)","journal-title":"IEEE Access"},{"issue":"12","key":"16_CR2","doi-asserted-by":"publisher","first-page":"2927","DOI":"10.3390\/s17122927","volume":"17","author":"V Cant\u00f3n Paterna","year":"2017","unstructured":"Cant\u00f3n Paterna, V., Calveras Auge, A., Paradells Aspas, J., et al.: A bluetooth low energy indoor positioning system with channel diversity, weighted trilateration and Kalman filtering. Sensors 17(12), 2927 (2017)","journal-title":"Sensors"},{"key":"16_CR3","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1016\/j.sigpro.2016.07.005","volume":"131","author":"S Yiu","year":"2016","unstructured":"Yiu, S., Dashti, M., Claussen, H., et al.: Wireless RSSI fingerprinting localization. Signal Process. 131, 235\u2013244 (2016)","journal-title":"Signal Process."},{"issue":"010","key":"16_CR4","first-page":"2461","volume":"038","author":"Y Xu","year":"2017","unstructured":"Xu, Y., Liu, H., Ma, Z., et al.: Multipath-tolerant ranging algorithm in underground tunnel for wireless sensor networks. Chin. J. Sci. Instrum. 038(010), 2461\u20132468 (2017)","journal-title":"Chin. J. Sci. Instrum."},{"issue":"8","key":"16_CR5","first-page":"133","volume":"46","author":"X Ni","year":"2019","unstructured":"Ni, X., Gao, Y., Li, L.: Hybrid filtering algorithm based on RSSI. Comput. Sci. 46(8), 133\u2013137 (2019)","journal-title":"Comput. Sci."},{"issue":"1","key":"16_CR6","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1109\/LCOMM.2015.2496940","volume":"20","author":"Y Li","year":"2016","unstructured":"Li, Y., Zhuang, Y., Lan, H., et al.: A hybrid WiFi\/magnetic matching\/PDR approach for indoor navigation with smartphone sensors. IEEE Commun. Lett. 20(1), 169\u2013172 (2016)","journal-title":"IEEE Commun. Lett."},{"key":"16_CR7","doi-asserted-by":"publisher","first-page":"26588","DOI":"10.1109\/ACCESS.2018.2837018","volume":"6","author":"W Xue","year":"2018","unstructured":"Xue, W., Hua, X., Li, Q., et al.: A new weighted algorithm based on the uneven spatial resolution of RSSI for indoor localization. IEEE Access 6, 26588\u201326595 (2018)","journal-title":"IEEE Access"},{"issue":"3","key":"16_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11277-017-4371-4","volume":"96","author":"C Zhou","year":"2017","unstructured":"Zhou, C., Yuan, J., Liu, H., et al.: Bluetooth indoor positioning based on RSSI and Kalman Filter. Wireless Pers. Commun. 96(3), 1\u201316 (2017)","journal-title":"Wireless Pers. Commun."},{"issue":"9","key":"16_CR9","doi-asserted-by":"publisher","first-page":"1830","DOI":"10.1109\/LCOMM.2018.2849963","volume":"22","author":"R Sari","year":"2018","unstructured":"Sari, R., Zayyani, H.: RSS localization using unknown statistical path loss exponent model. IEEE Commun. Lett. 22(9), 1830\u20131833 (2018)","journal-title":"IEEE Commun. Lett."},{"issue":"21","key":"16_CR10","doi-asserted-by":"publisher","first-page":"7762","DOI":"10.1109\/JSEN.2016.2600260","volume":"16","author":"LL Shen","year":"2016","unstructured":"Shen, L.L., Hui, W.W.S.: Improved pedestrian dead-reckoning-based indoor positioning by RSSI-based heading correction. IEEE Sens. J. 16(21), 7762\u20137773 (2016)","journal-title":"IEEE Sens. J."},{"key":"16_CR11","doi-asserted-by":"publisher","first-page":"26932","DOI":"10.1109\/ACCESS.2017.2778425","volume":"5","author":"B Zhang","year":"2017","unstructured":"Zhang, B., Wang, H., Zheng, L., et al.: Joint synchronization and localization for underwater sensor networks considering stratification effect. IEEE Access 5, 26932\u201326943 (2017)","journal-title":"IEEE Access"},{"key":"16_CR12","first-page":"50","volume":"1","author":"M Zhu","year":"2020","unstructured":"Zhu, M., Lu, X., Lu, Z., Li, Y., Tao, X.: RSSI indoor ranging algorithm combining wavelet transform and neural network. Bull. Surv. Mapp. 1, 50\u201354 (2020)","journal-title":"Bull. Surv. Mapp."},{"issue":"15","key":"16_CR13","doi-asserted-by":"publisher","first-page":"2253","DOI":"10.1049\/iet-com.2017.0429","volume":"11","author":"X Fang","year":"2017","unstructured":"Fang, X., Nan, L., Jiang, Z., et al.: Multi-channel fingerprint localisation algorithm for wireless sensor network in multipath environment. IET Commun. 11(15), 2253\u20132260 (2017)","journal-title":"IET Commun."},{"issue":"11","key":"16_CR14","doi-asserted-by":"publisher","first-page":"1934","DOI":"10.3390\/s16111934","volume":"16","author":"S Fengjun","year":"2016","unstructured":"Fengjun, S., Yi, J., Anping, X., et al.: A node localization algorithm based on multi-granularity regional division and the lagrange multiplier method in wireless sensor networks. Sensors 16(11), 1934 (2016)","journal-title":"Sensors"},{"issue":"1","key":"16_CR15","first-page":"167","volume":"40","author":"YF Ni","year":"2020","unstructured":"Ni, Y.F., Shi, X.H.: Indoor staff Kalman filter location algorithm based on RSSI. J. Xi\u2019an Univ. Sci. Technol. 40(1), 167\u2013172 (2020)","journal-title":"J. Xi\u2019an Univ. Sci. Technol."}],"container-title":["Lecture Notes in Computer Science","Spatial Data and Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-85462-1_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,14]],"date-time":"2021-08-14T06:05:07Z","timestamp":1628921107000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-85462-1_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030854614","9783030854621"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-85462-1_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"15 August 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SpatialDI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Spatial Data and Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hangzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 April 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 April 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"spatialdi2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/dbl.zju.edu.cn\/~yjgao\/spatialdi\/en\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"72","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"14","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"7","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"19% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}