{"id":"https://openalex.org/W2507292689","doi":"https://doi.org/10.1109/ivs.2016.7535491","title":"Track-constrained GNSS/odometer-based train localization using a particle filter","display_name":"Track-constrained GNSS/odometer-based train localization using a particle filter","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2507292689","doi":"https://doi.org/10.1109/ivs.2016.7535491","mag":"2507292689"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2016.7535491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2016.7535491","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101569349","display_name":"Jiang Liu","orcid":"https://orcid.org/0000-0002-2836-7651"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang Liu","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, Beijing, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636115","display_name":"Baigen Cai","orcid":"https://orcid.org/0000-0002-6440-005X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bai-gen Cai","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, Beijing, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100773356","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0003-1748-6409"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, Beijing, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"877","last_page":"882"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10655","display_name":"GNSS positioning and interference","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/odometer","display_name":"Odometer","score":0.9344670176506042},{"id":"https://openalex.org/keywords/gnss-applications","display_name":"GNSS applications","score":0.8525082468986511},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6707354784011841},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.62388676404953},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.5600369572639465},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.4856239855289459},{"id":"https://openalex.org/keywords/track","display_name":"Track (disk drive)","score":0.44676294922828674},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.4414905309677124},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4220009446144104},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4215913712978363},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.35822370648384094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2180163860321045},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1655779480934143},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1102973222732544},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09459754824638367}],"concepts":[{"id":"https://openalex.org/C93717769","wikidata":"https://www.wikidata.org/wiki/Q745105","display_name":"Odometer","level":2,"score":0.9344670176506042},{"id":"https://openalex.org/C14279187","wikidata":"https://www.wikidata.org/wiki/Q5514012","display_name":"GNSS applications","level":3,"score":0.8525082468986511},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6707354784011841},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.62388676404953},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.5600369572639465},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.4856239855289459},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.44676294922828674},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.4414905309677124},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4220009446144104},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4215913712978363},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.35822370648384094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2180163860321045},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1655779480934143},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1102973222732544},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09459754824638367},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2016.7535491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2016.7535491","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1493134128","https://openalex.org/W1583534636","https://openalex.org/W1985602662","https://openalex.org/W1995957864","https://openalex.org/W2001342444","https://openalex.org/W2024323125","https://openalex.org/W2045182441","https://openalex.org/W2054091988","https://openalex.org/W2067738919","https://openalex.org/W2082649086","https://openalex.org/W2104649107","https://openalex.org/W2126788637","https://openalex.org/W2160337655","https://openalex.org/W2379544063","https://openalex.org/W6629457601","https://openalex.org/W6635154881","https://openalex.org/W6675880244","https://openalex.org/W7024581827"],"related_works":["https://openalex.org/W4323767814","https://openalex.org/W4387698348","https://openalex.org/W2115775154","https://openalex.org/W1964715412","https://openalex.org/W2282123131","https://openalex.org/W2346939607","https://openalex.org/W2990396425","https://openalex.org/W3001939774","https://openalex.org/W1585960250","https://openalex.org/W2341297234"],"abstract_inverted_index":{"The":[0,145],"accurate":[1,94],"and":[2,25,64,140,186],"reliable":[3],"localization":[4,39,183],"of":[5,15,23,55,67,96,147,162,176],"the":[6,21,27,45,52,56,61,65,68,79,85,97,117,126,131,154,159,163,174,177,195],"trains":[7],"is":[8,33,58,71,89,108,122,150,189],"one":[9],"decisive":[10],"factor":[11],"for":[12,37,158,181,193],"a":[13,136],"lot":[14],"specific":[16],"location-based":[17],"railway":[18,199],"applications.":[19],"Considering":[20],"cost-efficiency":[22],"construction":[24],"maintenance,":[26],"Global":[28],"Navigation":[29],"Satellite":[30],"System":[31],"(GNSS)":[32],"an":[34,93,103,141],"effective":[35],"approach":[36],"train":[38,182],"systems":[40],"which":[41,134,188],"aim":[42],"to":[43,76,91,110,124,152],"replace":[44],"track-side":[46],"Balises":[47],"with":[48,78,170,190],"on-board":[49,69],"sensors.":[50],"Thus,":[51],"accumulative":[53],"error":[54],"odometer":[57],"calibrated":[59],"by":[60,129],"GNSS":[62,185],"receivers":[63],"autonomy":[66],"equipment":[70],"surely":[72],"improved.":[73],"In":[74,114],"order":[75],"cope":[77],"uncertainties":[80],"in":[81],"raw":[82],"sensor":[83],"measurements,":[84],"Bayesian":[86],"filtering":[87],"frame":[88],"adopted":[90],"obtain":[92],"estimation":[95],"train's":[98],"state.":[99],"Based":[100],"on":[101],"that,":[102],"enhanced":[104],"particle":[105,179],"filter":[106,120,180],"solution":[107],"presented":[109],"realize":[111],"iterative":[112],"estimation.":[113],"this":[115],"method,":[116],"cubature":[118],"Kalman":[119],"(CKF)":[121],"involved":[123],"generate":[125,153],"proposal":[127,156],"distribution":[128,157],"using":[130,184],"track":[132,148],"constraint,":[133],"indicates":[135],"modified":[137],"kinematical":[138],"model":[139],"extended":[142],"measurement":[143],"model.":[144],"coupling":[146],"constraint":[149],"designed":[151],"importance":[155,165],"update":[160],"stage":[161],"sequential":[164],"sampling.":[166],"Results":[167],"from":[168],"simulation":[169],"field":[171],"data":[172],"demonstrate":[173],"capability":[175],"track-constrained":[178],"odometer,":[187],"great":[191],"potential":[192],"enabling":[194],"next":[196],"generation":[197],"GNSS-based":[198],"systems.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}