{"id":"https://openalex.org/W2548457765","doi":"https://doi.org/10.1109/igarss.2016.7730730","title":"Multi-aperture anomaly detector for clutter background","display_name":"Multi-aperture anomaly detector for clutter background","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2548457765","doi":"https://doi.org/10.1109/igarss.2016.7730730","mag":"2548457765"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2016.7730730","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7730730","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","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/A5101816654","display_name":"Min Li","orcid":"https://orcid.org/0000-0002-6724-825X"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Min Li","raw_affiliation_strings":["Collage of IOT, Hohai University, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Collage of IOT, Hohai University, Jiangsu, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101942262","display_name":"Xinnan Fan","orcid":"https://orcid.org/0009-0002-1061-3209"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinnan Fan","raw_affiliation_strings":["Collage of IOT, Hohai University, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Collage of IOT, Hohai University, Jiangsu, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100768031","display_name":"Xuewu Zhang","orcid":"https://orcid.org/0000-0001-6214-880X"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuewu Zhang","raw_affiliation_strings":["Collage of IOT, Hohai University, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Collage of IOT, Hohai University, Jiangsu, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045561301","display_name":"Puhuang Li","orcid":null},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Puhuang Li","raw_affiliation_strings":["Collage of IOT, Hohai University, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Collage of IOT, Hohai University, Jiangsu, China","institution_ids":["https://openalex.org/I163340411"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101816654"],"corresponding_institution_ids":["https://openalex.org/I163340411"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16793937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6625","last_page":"6628"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.993399977684021,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9850999712944031,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6863961219787598},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.6570727229118347},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6359740495681763},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5974298715591431},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5374354124069214},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4852309226989746},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48179739713668823},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.4592374265193939},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.4480752944946289},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4328208267688751},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4319613575935364},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36893796920776367},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.25534874200820923},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.08508467674255371}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6863961219787598},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.6570727229118347},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6359740495681763},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5974298715591431},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5374354124069214},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4852309226989746},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48179739713668823},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.4592374265193939},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.4480752944946289},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4328208267688751},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4319613575935364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36893796920776367},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.25534874200820923},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.08508467674255371},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2016.7730730","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7730730","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","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":14,"referenced_works":["https://openalex.org/W1971358070","https://openalex.org/W1998691552","https://openalex.org/W2002189870","https://openalex.org/W2057498097","https://openalex.org/W2067782748","https://openalex.org/W2082938722","https://openalex.org/W2121824258","https://openalex.org/W2122646361","https://openalex.org/W2124267685","https://openalex.org/W2124463804","https://openalex.org/W2140340527","https://openalex.org/W2142552707","https://openalex.org/W2158340226","https://openalex.org/W6664921363"],"related_works":["https://openalex.org/W2388326001","https://openalex.org/W3011102797","https://openalex.org/W4320921117","https://openalex.org/W2351401443","https://openalex.org/W2115015615","https://openalex.org/W1968850503","https://openalex.org/W1649651896","https://openalex.org/W2116961228","https://openalex.org/W1952514008","https://openalex.org/W4387803549"],"abstract_inverted_index":{"Without":[0,114],"priori":[1],"information,":[2],"anomaly":[3,16,37,85,107,125,170,206],"detector":[4,108,126],"has":[5,204],"more":[6,43,45,197],"important":[7],"utility":[8],"compared":[9],"with":[10,34,134],"supervised":[11],"target":[12],"detection.":[13],"Many":[14],"classical":[15],"detectors":[17],"have":[18,28,49],"obtained":[19],"perfect":[20],"performance":[21],"in":[22,111],"many":[23],"situations.":[24],"However,":[25],"there":[26],"still":[27],"two":[29,103],"problems":[30],"which":[31,48,65,158,203],"are":[32],"correlated":[33],"accuracy":[35],"of":[36,57,74,77,84,116,150,162,166,188],"detector.":[38],"Firstly,":[39],"clutter":[40,58,135],"background":[41,59,70,79],"induced":[42],"and":[44,119,180],"difficult":[46],"pixel":[47],"moderate":[50,205],"statistical":[51,121],"difference.":[52],"Then,":[53,169],"ideal":[54],"uncontaminated":[55],"subset":[56],"is":[60,66,89,94,109,127,143,172,196],"hard":[61],"to":[62,68,129,174,199,215],"be":[63,154,213],"obtain":[64],"used":[67,214],"estimate":[69],"model.":[71],"Secondly,":[72],"difference":[73,177],"spectral":[75,160,167],"content":[76],"different":[78,217],"objects":[80],"will":[81,153],"effect":[82],"salience":[83,171],"targets.":[86],"And":[87],"it":[88],"arbitrary":[90],"that":[91],"uncertain":[92],"pixels":[93,118,179,202],"nominated":[95],"as":[96,156],"non-anomalies":[97],"by":[98,145],"one":[99],"threshold.":[100],"For":[101],"above":[102],"problems,":[104],"a":[105,163],"multi-aperture":[106,138],"proposed":[110,124,173],"this":[112],"paper.":[113],"selection":[115],"anomaly-free":[117],"accurate":[120],"model,":[122],"the":[123,176,184],"expected":[128],"decrease":[130],"false":[131],"alarm":[132],"rate":[133],"background.":[136],"A":[137],"division":[139],"for":[140],"hyperspectral":[141],"cube":[142],"conducted":[144],"iterative":[146],"process.":[147],"Statistical":[148],"data":[149],"ever":[151],"subaperture":[152],"named":[155],"basis,":[157],"represent":[159],"characteristic":[161],"certain":[164],"range":[165],"cube.":[168],"measure":[175],"between":[178],"sub-aperture":[181],"basis.":[182],"On":[183],"other":[185],"hand,":[186],"continuity":[187],"membership":[189],"value":[190],"based":[191],"on":[192],"fuzzy":[193],"logical":[194],"theory":[195],"suitable":[198],"nominate":[200],"difficulty":[201],"salience.":[207],"At":[208],"last":[209],"defuzzification":[210],"ruler":[211],"can":[212],"fuse":[216],"detection":[218],"results":[219],"from":[220],"multi-aperture.":[221]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}