{"id":"https://openalex.org/W4408017244","doi":"https://doi.org/10.1109/lwc.2025.3546228","title":"An ARIMA-Based Autonomous Underwater Vehicle Tracking Algorithm","display_name":"An ARIMA-Based Autonomous Underwater Vehicle Tracking Algorithm","publication_year":2025,"publication_date":"2025-02-27","ids":{"openalex":"https://openalex.org/W4408017244","doi":"https://doi.org/10.1109/lwc.2025.3546228"},"language":"en","primary_location":{"id":"doi:10.1109/lwc.2025.3546228","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2025.3546228","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Wireless Communications Letters","raw_type":"journal-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/A5100413844","display_name":"Ming Xu","orcid":"https://orcid.org/0000-0001-5054-301X"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Xu","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-5054-301X","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jianfei Wu","orcid":"https://orcid.org/0009-0003-6928-8233"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfei Wu","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0003-6928-8233","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai, China","institution_ids":["https://openalex.org/I96733725"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I96733725"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03959551,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"5","first_page":"1481","last_page":"1485"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.9571999907493591,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11622","display_name":"Maritime Navigation and Safety","score":0.9571999907493591,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9562000036239624,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9294000267982483,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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-science","display_name":"Computer science","score":0.6406630873680115},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.5691365003585815},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.5394718050956726},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.49724701046943665},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41355186700820923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3864787220954895},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3636663258075714},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3209088146686554},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.21466666460037231},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.13202348351478577}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6406630873680115},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.5691365003585815},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.5394718050956726},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.49724701046943665},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41355186700820923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3864787220954895},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3636663258075714},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3209088146686554},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.21466666460037231},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.13202348351478577},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lwc.2025.3546228","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2025.3546228","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Wireless Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7660232414","display_name":null,"funder_award_id":"62172269","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2951837999","https://openalex.org/W2964263863","https://openalex.org/W3002104503","https://openalex.org/W3149903970","https://openalex.org/W3155953919","https://openalex.org/W3192389740","https://openalex.org/W3199833714","https://openalex.org/W3207822900","https://openalex.org/W3213336033","https://openalex.org/W4323644337","https://openalex.org/W4391132066","https://openalex.org/W4392581112","https://openalex.org/W4398151017","https://openalex.org/W4401742364"],"related_works":["https://openalex.org/W3135881084","https://openalex.org/W2380590035","https://openalex.org/W2351712633","https://openalex.org/W4388984322","https://openalex.org/W4285509495","https://openalex.org/W1509694164","https://openalex.org/W3216381689","https://openalex.org/W4224133501","https://openalex.org/W2158788032","https://openalex.org/W2103825597"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,36,58,109],"track":[3,143],"the":[4,38,43,60,65,70,85,90,116,119,125,134,144],"Autonomous":[5],"Underwater":[6],"Vehicles":[7],"(AUVs)":[8],"in":[9,84,94,148],"highly":[10],"noisy":[11],"underwater":[12,96,153],"environments,":[13],"we":[14,28,53,99],"propose":[15,29,100],"an":[16,30],"AutoRegressive":[17],"Integrated":[18],"Moving":[19],"Average-based":[20],"AUV":[21,61],"Tracking":[22],"Algorithm,":[23],"coined":[24],"as":[25],"ARIMA-AT.":[26],"First,":[27],"atomic":[31],"norm":[32],"minimization-based":[33],"beamforming":[34,56],"approach":[35],"enhance":[37],"prediction":[39,107,139],"accuracy":[40,117],"by":[41,46],"addressing":[42],"limitations":[44],"posed":[45],"sparse":[47],"and":[48,88,123,141],"incomplete":[49],"sensor":[50],"data.":[51],"Second,":[52],"construct":[54],"a":[55,74,101],"model":[57,79],"predict":[59,110],"trajectory":[62],"based":[63,105],"on":[64],"ARIMA":[66,120],"framework,":[67],"which":[68],"minimizes":[69],"parameter":[71,106,121],"error":[72],"using":[73],"Lagrange":[75],"multiplier":[76],"method.":[77],"This":[78],"accounts":[80],"for":[81,113],"temporal":[82],"dependencies":[83],"AUV\u2019s":[86],"movement":[87,145],"improves":[89],"robustness":[91],"of":[92,118,127,146],"tracking":[93],"dynamic":[95],"environments.":[97,154],"Third,":[98],"Fisher":[102],"information":[103],"matrix":[104],"method":[108],"ARIMA-AT":[111,135],"parameters":[112],"further":[114],"refining":[115],"estimation":[122],"reducing":[124],"impact":[126],"noise":[128],"interference.":[129],"Experimental":[130],"results":[131],"demonstrate":[132],"that":[133],"algorithm":[136],"can":[137],"reduce":[138],"errors":[140],"accurately":[142],"AUVs":[147],"low":[149],"signal-to-noise":[150],"ratio":[151],"(SNR)":[152]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}