{"id":"https://openalex.org/W2080655172","doi":"https://doi.org/10.1109/pimrc.2010.5672056","title":"Does particle filter really outperform low pass filter in indoor target tracking?","display_name":"Does particle filter really outperform low pass filter in indoor target tracking?","publication_year":2010,"publication_date":"2010-09-01","ids":{"openalex":"https://openalex.org/W2080655172","doi":"https://doi.org/10.1109/pimrc.2010.5672056","mag":"2080655172"},"language":"en","primary_location":{"id":"doi:10.1109/pimrc.2010.5672056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc.2010.5672056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications","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/A5072614620","display_name":"Daisuke Anzai","orcid":"https://orcid.org/0000-0003-4872-1539"},"institutions":[{"id":"https://openalex.org/I317356780","display_name":"Osaka City University","ror":"https://ror.org/02skfsw40","country_code":"JP","type":"education","lineage":["https://openalex.org/I317356780"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daisuke Anzai","raw_affiliation_strings":["Graduate School of Engineering, Osaka City University, Sumiyoshi, Osaka, Japan","Graduate School of Engineering, Osaka City University, 3-3-138, Sugimototyou, Sumiyoshi-ku, 558-8585, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Osaka City University, Sumiyoshi, Osaka, Japan","institution_ids":["https://openalex.org/I317356780"]},{"raw_affiliation_string":"Graduate School of Engineering, Osaka City University, 3-3-138, Sugimototyou, Sumiyoshi-ku, 558-8585, Japan","institution_ids":["https://openalex.org/I317356780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061363370","display_name":"Shinsuke Hara","orcid":"https://orcid.org/0000-0002-5183-9725"},"institutions":[{"id":"https://openalex.org/I317356780","display_name":"Osaka City University","ror":"https://ror.org/02skfsw40","country_code":"JP","type":"education","lineage":["https://openalex.org/I317356780"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shinsuke Hara","raw_affiliation_strings":["Graduate School of Engineering, Osaka City University, Sumiyoshi, Osaka, Japan","Graduate School of Engineering, Osaka City University, 3-3-138, Sugimototyou, Sumiyoshi-ku, 558-8585, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Osaka City University, Sumiyoshi, Osaka, Japan","institution_ids":["https://openalex.org/I317356780"]},{"raw_affiliation_string":"Graduate School of Engineering, Osaka City University, 3-3-138, Sugimototyou, Sumiyoshi-ku, 558-8585, Japan","institution_ids":["https://openalex.org/I317356780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I317356780"],"apc_list":null,"apc_paid":null,"fwci":0.8174,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72041767,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"56","issue":null,"first_page":"882","last_page":"886"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9988999962806702,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/infinite-impulse-response","display_name":"Infinite impulse response","score":0.7133346796035767},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.7022340297698975},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6306902170181274},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.5876470804214478},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5763200521469116},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5642907619476318},{"id":"https://openalex.org/keywords/low-pass-filter","display_name":"Low-pass filter","score":0.5375440120697021},{"id":"https://openalex.org/keywords/2d-filters","display_name":"2D Filters","score":0.5058671832084656},{"id":"https://openalex.org/keywords/filter-design","display_name":"Filter design","score":0.48054391145706177},{"id":"https://openalex.org/keywords/digital-filter","display_name":"Digital filter","score":0.3452650308609009},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.31929880380630493},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26787251234054565}],"concepts":[{"id":"https://openalex.org/C183816354","wikidata":"https://www.wikidata.org/wiki/Q665617","display_name":"Infinite impulse response","level":4,"score":0.7133346796035767},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.7022340297698975},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6306902170181274},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.5876470804214478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5763200521469116},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5642907619476318},{"id":"https://openalex.org/C44682112","wikidata":"https://www.wikidata.org/wiki/Q918242","display_name":"Low-pass filter","level":3,"score":0.5375440120697021},{"id":"https://openalex.org/C100106864","wikidata":"https://www.wikidata.org/wiki/Q16001029","display_name":"2D Filters","level":5,"score":0.5058671832084656},{"id":"https://openalex.org/C22597639","wikidata":"https://www.wikidata.org/wiki/Q5449227","display_name":"Filter design","level":3,"score":0.48054391145706177},{"id":"https://openalex.org/C36390408","wikidata":"https://www.wikidata.org/wiki/Q1163067","display_name":"Digital filter","level":3,"score":0.3452650308609009},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.31929880380630493},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26787251234054565},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pimrc.2010.5672056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc.2010.5672056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1633983593","https://openalex.org/W2018550241","https://openalex.org/W2044006304","https://openalex.org/W2057722975","https://openalex.org/W2098499401","https://openalex.org/W2114632122","https://openalex.org/W2123638939","https://openalex.org/W2136432122","https://openalex.org/W2142760360","https://openalex.org/W2160337655","https://openalex.org/W2163817142","https://openalex.org/W2296013757","https://openalex.org/W6677075764"],"related_works":["https://openalex.org/W605224089","https://openalex.org/W2741663537","https://openalex.org/W2163092165","https://openalex.org/W1925343219","https://openalex.org/W2183200629","https://openalex.org/W2066938466","https://openalex.org/W433445967","https://openalex.org/W2347800965","https://openalex.org/W2117997928","https://openalex.org/W4301184722"],"abstract_inverted_index":{"This":[0],"paper":[1],"compares":[2],"the":[3,28,32,39,44,47,53,61,65,68,81,85,91,97],"indoor":[4],"tracking":[5,50,58,102,118],"performance":[6],"for":[7],"a":[8,21,35,71],"moving":[9],"target":[10,36,72],"between":[11],"an":[12],"IIR":[13,54,86,98],"(Infinite":[14],"Impulse":[15],"Response)":[16],"low":[17,55,87,99],"pass":[18,56,88,100],"filter":[19,89],"and":[20,76,115],"particle":[22,45,48,92],"filter.":[23,93],"It":[24,94],"reveals":[25],"that,":[26],"in":[27,43,64,106],"computer":[29],"simulations":[30],"where":[31,67],"motion":[33,69],"of":[34,70],"exactly":[37],"follows":[38],"state":[40,82],"transition":[41,83],"model":[42],"filter,":[46],"filter-based":[49,57,101],"system":[51,103],"outperforms":[52,90],"system.":[59],"On":[60],"other":[62],"hand,":[63],"experiments":[66],"is":[73,104],"really":[74],"unpredictable":[75],"does":[77],"not":[78],"always":[79],"follow":[80],"model,":[84],"concludes":[95],"that":[96],"advantageous":[105],"reality,":[107],"because":[108],"it":[109],"requires":[110],"far":[111],"less":[112],"computational":[113],"cost":[114],"shows":[116],"better":[117],"performance.":[119]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}