{"id":"https://openalex.org/W2005741311","doi":"https://doi.org/10.1109/camsap.2013.6714022","title":"RSS-based sensor network localization in contaminated Gaussian measurement noise","display_name":"RSS-based sensor network localization in contaminated Gaussian measurement noise","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W2005741311","doi":"https://doi.org/10.1109/camsap.2013.6714022","mag":"2005741311"},"language":"en","primary_location":{"id":"doi:10.1109/camsap.2013.6714022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap.2013.6714022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121629","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100696174","display_name":"Feng Yin","orcid":"https://orcid.org/0000-0001-5754-9246"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Feng Yin","raw_affiliation_strings":["Signal Processing Group, Technische Universit\u00e4t Darmstadt, Germany","Signal Process. Group, Tech. Univ. Darmstadt, Darmstadt, Germany"],"affiliations":[{"raw_affiliation_string":"Signal Processing Group, Technische Universit\u00e4t Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]},{"raw_affiliation_string":"Signal Process. Group, Tech. Univ. Darmstadt, Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100413655","display_name":"Ang Li","orcid":"https://orcid.org/0000-0003-2385-6963"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ang Li","raw_affiliation_strings":["Signal Processing Group, Technische Universit\u00e4t Darmstadt, Germany","Signal Process. Group, Tech. Univ. Darmstadt, Darmstadt, Germany"],"affiliations":[{"raw_affiliation_string":"Signal Processing Group, Technische Universit\u00e4t Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]},{"raw_affiliation_string":"Signal Process. Group, Tech. Univ. Darmstadt, Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001328562","display_name":"Abdelhak M. Zoubir","orcid":"https://orcid.org/0000-0002-4409-7743"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Abdelhak M. Zoubir","raw_affiliation_strings":["Signal Processing Group, Technische Universit\u00e4t Darmstadt, Germany","Signal Process. Group, Tech. Univ. Darmstadt, Darmstadt, Germany"],"affiliations":[{"raw_affiliation_string":"Signal Processing Group, Technische Universit\u00e4t Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]},{"raw_affiliation_string":"Signal Process. Group, Tech. Univ. Darmstadt, Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000005967","display_name":"Carsten Fritsche","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carsten Fritsche","raw_affiliation_strings":["IFEN GmbH, Poing, Germany"],"affiliations":[{"raw_affiliation_string":"IFEN GmbH, Poing, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058002446","display_name":"Fredrik Gustafsson","orcid":"https://orcid.org/0000-0003-3270-171X"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Fredrik Gustafsson","raw_affiliation_strings":["Division of Automatic Control, Link\u00f6ping University, Sweden","Div. of Autom. Control, Linkoping Univ., Link\u00f6ping, Sweden#TAB#"],"affiliations":[{"raw_affiliation_string":"Division of Automatic Control, Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]},{"raw_affiliation_string":"Div. of Autom. Control, Linkoping Univ., Link\u00f6ping, Sweden#TAB#","institution_ids":["https://openalex.org/I102134673"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100696174"],"corresponding_institution_ids":["https://openalex.org/I31512782"],"apc_list":null,"apc_paid":null,"fwci":0.4729,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.68021393,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"39","issue":null,"first_page":"121","last_page":"124"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9987000226974487,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/rss","display_name":"RSS","score":0.7671289443969727},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.6791900992393494},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6694821119308472},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6667748689651489},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6465874910354614},{"id":"https://openalex.org/keywords/cram\u00e9r\u2013rao-bound","display_name":"Cram\u00e9r\u2013Rao bound","score":0.6422330737113953},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.6034405827522278},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5928024053573608},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5916773676872253},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5309417247772217},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5253583788871765},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45709294080734253},{"id":"https://openalex.org/keywords/gaussian-network-model","display_name":"Gaussian network model","score":0.4151366353034973},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4121624827384949},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3387354016304016},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.2876783013343811},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.23793992400169373},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21757575869560242},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.169497549533844},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07829439640045166}],"concepts":[{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.7671289443969727},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.6791900992393494},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6694821119308472},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6667748689651489},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6465874910354614},{"id":"https://openalex.org/C4978587","wikidata":"https://www.wikidata.org/wiki/Q1138810","display_name":"Cram\u00e9r\u2013Rao bound","level":3,"score":0.6422330737113953},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.6034405827522278},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5928024053573608},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5916773676872253},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5309417247772217},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5253583788871765},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45709294080734253},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.4151366353034973},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4121624827384949},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3387354016304016},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2876783013343811},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.23793992400169373},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21757575869560242},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.169497549533844},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07829439640045166},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/camsap.2013.6714022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap.2013.6714022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","raw_type":"proceedings-article"},{"id":"pmh:oai:DiVA.org:liu-121629","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121629","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:liu-121629","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121629","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1983874789","https://openalex.org/W2030176049","https://openalex.org/W2049633694","https://openalex.org/W2095705027","https://openalex.org/W2114351513","https://openalex.org/W2120048446","https://openalex.org/W2124178852","https://openalex.org/W2126286199","https://openalex.org/W2308181013","https://openalex.org/W4292403327"],"related_works":["https://openalex.org/W4224323762","https://openalex.org/W2986378528","https://openalex.org/W4388692784","https://openalex.org/W3178345791","https://openalex.org/W1550854977","https://openalex.org/W2092661960","https://openalex.org/W4231055618","https://openalex.org/W2949211747","https://openalex.org/W3005742472","https://openalex.org/W2162441712"],"abstract_inverted_index":{"We":[0,11,41],"study":[1],"received":[2],"signal":[3],"strength-based":[4],"cooperative":[5],"localization":[6,51,64],"in":[7,66],"wireless":[8],"sensor":[9],"networks.":[10],"assume":[12],"that":[13],"the":[14,61,69,75,78],"measurement":[15],"noise":[16],"fits":[17],"a":[18],"contaminated":[19],"Gaussian":[20],"model":[21],"so":[22],"as":[23,81],"to":[24,38,83],"take":[25],"into":[26],"account":[27],"some":[28,33,84],"outlier":[29],"conditions.":[30],"In":[31],"addition,":[32],"environment-dependent":[34],"parameters":[35],"are":[36],"assumed":[37],"be":[39],"unknown.":[40],"propose":[42],"an":[43],"expectation-maximization":[44],"based":[45],"algorithm":[46,80],"for":[47,57],"robust":[48],"centralized":[49],"network":[50],"without":[52],"offline":[53],"training.":[54],"As":[55],"benchmark":[56],"comparison,":[58],"we":[59],"express":[60],"best":[62],"achievable":[63],"accuracy":[65],"terms":[67],"of":[68,77],"Cram\u00e9r-Rao":[70],"bound.":[71],"Experimental":[72],"results":[73],"demonstrate":[74],"advantages":[76],"proposed":[79],"compared":[82],"representative":[85],"algorithms.":[86]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}
