{"id":"https://openalex.org/W3132543077","doi":"https://doi.org/10.1109/iros45743.2020.9341410","title":"Bayesian Fusion of Unlabeled Vision and RF Data for Aerial Tracking of Ground Targets","display_name":"Bayesian Fusion of Unlabeled Vision and RF Data for Aerial Tracking of Ground Targets","publication_year":2020,"publication_date":"2020-10-24","ids":{"openalex":"https://openalex.org/W3132543077","doi":"https://doi.org/10.1109/iros45743.2020.9341410","mag":"3132543077"},"language":"en","primary_location":{"id":"doi:10.1109/iros45743.2020.9341410","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9341410","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"article","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/A5081800215","display_name":"Ramya Kanlapuli Rajasekaran","orcid":null},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ramya Kanlapuli Rajasekaran","raw_affiliation_strings":["University of Colorado Boulder, Boulder, Colorado"],"affiliations":[{"raw_affiliation_string":"University of Colorado Boulder, Boulder, Colorado","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100664008","display_name":"Nisar Ahmed","orcid":"https://orcid.org/0000-0002-7555-5671"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nisar Ahmed","raw_affiliation_strings":["University of Colorado Boulder, Boulder, Colorado"],"affiliations":[{"raw_affiliation_string":"University of Colorado Boulder, Boulder, Colorado","institution_ids":["https://openalex.org/I188538660"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021878663","display_name":"Eric W. Frew","orcid":"https://orcid.org/0000-0003-3686-089X"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eric Frew","raw_affiliation_strings":["University of Colorado Boulder, Boulder, Colorado"],"affiliations":[{"raw_affiliation_string":"University of Colorado Boulder, Boulder, Colorado","institution_ids":["https://openalex.org/I188538660"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081800215"],"corresponding_institution_ids":["https://openalex.org/I188538660"],"apc_list":null,"apc_paid":null,"fwci":0.3977,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70539256,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"19","issue":null,"first_page":"1629","last_page":"1636"},"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":0.9993000030517578,"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":0.9993000030517578,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9976999759674072,"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"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9853000044822693,"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/computer-vision","display_name":"Computer vision","score":0.7726367115974426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.754848837852478},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6959825158119202},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.6368795037269592},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6340329647064209},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6148281693458557},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.4796505272388458},{"id":"https://openalex.org/keywords/radio-frequency","display_name":"Radio frequency","score":0.46246713399887085},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.44796374440193176},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.42453569173812866},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.3703085780143738},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.30561089515686035}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7726367115974426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.754848837852478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6959825158119202},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.6368795037269592},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6340329647064209},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6148281693458557},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.4796505272388458},{"id":"https://openalex.org/C74064498","wikidata":"https://www.wikidata.org/wiki/Q3396184","display_name":"Radio frequency","level":2,"score":0.46246713399887085},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.44796374440193176},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.42453569173812866},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3703085780143738},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.30561089515686035},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros45743.2020.9341410","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9341410","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320333620","display_name":"Center for Unmanned Aircraft Systems","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1501529171","https://openalex.org/W2001110635","https://openalex.org/W2015697476","https://openalex.org/W2028683273","https://openalex.org/W2033732379","https://openalex.org/W2044719482","https://openalex.org/W2118603200","https://openalex.org/W2139123921","https://openalex.org/W2160337655","https://openalex.org/W2167582467","https://openalex.org/W2220074677","https://openalex.org/W2313801535","https://openalex.org/W2569306753","https://openalex.org/W2758135839","https://openalex.org/W2885102548","https://openalex.org/W2891949671","https://openalex.org/W2892608409","https://openalex.org/W2897884082","https://openalex.org/W2910147756","https://openalex.org/W2913333570","https://openalex.org/W2972345018","https://openalex.org/W6680792525","https://openalex.org/W6683341698","https://openalex.org/W6757982023"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W1496493270","https://openalex.org/W1981531423","https://openalex.org/W2011939812","https://openalex.org/W1977371217","https://openalex.org/W2115214301","https://openalex.org/W4295296093"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,24,64,99],"method":[4],"for":[5,115,157],"target":[6,73,103,130,149],"localization":[7],"and":[8,17,38,68,134,151,168],"tracking":[9,36],"in":[10,40,63],"clutter":[11],"using":[12,53],"Bayesian":[13],"fusion":[14,31,178],"of":[15,42,61,94,172],"vision":[16],"Radio":[18],"Frequency":[19],"(RF)":[20],"sensors":[21],"used":[22,33],"aboard":[23],"small":[25],"Unmanned":[26],"Aircraft":[27],"System":[28],"(sUAS).":[29],"Sensor":[30],"is":[32,51,83,120,142],"to":[34,75,98,110,125,145,166],"ensure":[35],"robustness":[37],"reliability":[39],"case":[41],"camera":[43],"occlusion":[44],"or":[45],"RF":[46,71,132,152,174],"signal":[47],"interference.":[48],"Camera":[49],"data":[50,86,112,133,177],"processed":[52],"an":[54],"off-the-shelf":[55],"algorithm":[56],"that":[57],"detects":[58],"possible":[59],"objects":[60],"interest":[62],"given":[65],"image":[66],"frame,":[67],"the":[69,91,95,170,173],"true":[70],"emitting":[72],"needs":[74],"be":[76],"identified":[77],"from":[78],"among":[79],"these":[80],"if":[81],"it":[82],"present.":[84],"These":[85],"sources,":[87],"as":[88,90],"well":[89],"unknown":[92],"motion":[93],"target,":[96],"lead":[97],"heavily":[100],"non-linear":[101],"non-Gaussian":[102],"state":[104],"uncertainties,":[105],"which":[106],"are":[107,164],"not":[108],"amenable":[109],"typical":[111],"association":[113,154],"methods":[114],"tracking.":[116],"A":[117,138],"probabilistic":[118],"model":[119,162],"thus":[121],"first":[122],"rigorously":[123],"developed":[124,144],"relate":[126],"conditional":[127],"dependencies":[128],"between":[129],"movements,":[131],"visual":[135,158,176],"object":[136,159],"detections.":[137,160],"modified":[139],"particle":[140],"filter":[141],"then":[143],"simultaneously":[146],"reason":[147],"over":[148],"states":[150],"emitter":[153],"hypothesis":[155],"labels":[156],"Truth":[161],"simulations":[163],"presented":[165],"compare":[167],"validate":[169],"effectiveness":[171],"+":[175],"filter.":[179]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}