{"id":"https://openalex.org/W4402680001","doi":"https://doi.org/10.1145/3653644.3664958","title":"Frequency Diverse Coprime MIMO radar for Angle-Range Estimation","display_name":"Frequency Diverse Coprime MIMO radar for Angle-Range Estimation","publication_year":2024,"publication_date":"2024-04-26","ids":{"openalex":"https://openalex.org/W4402680001","doi":"https://doi.org/10.1145/3653644.3664958"},"language":"en","primary_location":{"id":"doi:10.1145/3653644.3664958","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3653644.3664958","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd International Conference on Frontiers of Artificial Intelligence and Machine Learning","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/A5018065582","display_name":"Yuehao Guo","orcid":"https://orcid.org/0000-0002-4042-2609"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuehao Guo","raw_affiliation_strings":["Hainan University, China"],"affiliations":[{"raw_affiliation_string":"Hainan University, China","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101947451","display_name":"Xianpeng Wang","orcid":"https://orcid.org/0000-0002-6681-6489"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianpeng Wang","raw_affiliation_strings":["Hainan University, China"],"affiliations":[{"raw_affiliation_string":"Hainan University, China","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082609933","display_name":"Linqiang Wen","orcid":"https://orcid.org/0009-0001-4150-0605"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linqiang Wen","raw_affiliation_strings":["Hainan University, China"],"affiliations":[{"raw_affiliation_string":"Hainan University, China","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071225765","display_name":"Wenshuai Wang","orcid":"https://orcid.org/0009-0009-5181-2504"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenshuai Wang","raw_affiliation_strings":["Hainan University, China"],"affiliations":[{"raw_affiliation_string":"Hainan University, China","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100922730","display_name":"Yuan Wang","orcid":"https://orcid.org/0009-0007-0845-1315"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Wang","raw_affiliation_strings":["Hainan University, China"],"affiliations":[{"raw_affiliation_string":"Hainan University, China","institution_ids":["https://openalex.org/I20942203"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018065582"],"corresponding_institution_ids":["https://openalex.org/I20942203"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21609995,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"117","last_page":"121"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10891","display_name":"Radar Systems and Signal Processing","score":1.0,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9994999766349792,"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/range","display_name":"Range (aeronautics)","score":0.5489559173583984},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.5228862166404724},{"id":"https://openalex.org/keywords/coprime-integers","display_name":"Coprime integers","score":0.5218899846076965},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5036856532096863},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4982895851135254},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3824324309825897},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.27332258224487305},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.2128959596157074},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21095165610313416},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18195801973342896},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.16007274389266968},{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.10432097315788269}],"concepts":[{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5489559173583984},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.5228862166404724},{"id":"https://openalex.org/C23230895","wikidata":"https://www.wikidata.org/wiki/Q104752","display_name":"Coprime integers","level":2,"score":0.5218899846076965},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5036856532096863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4982895851135254},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3824324309825897},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27332258224487305},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2128959596157074},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21095165610313416},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18195801973342896},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.16007274389266968},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.10432097315788269}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3653644.3664958","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3653644.3664958","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd International Conference on Frontiers of Artificial Intelligence and Machine Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.5699999928474426}],"awards":[{"id":"https://openalex.org/G1989119900","display_name":null,"funder_award_id":"620RC555","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G6816392984","display_name":null,"funder_award_id":"ZDYF2023GXJS159","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2003157621","https://openalex.org/W2004944703","https://openalex.org/W2110798624","https://openalex.org/W2164390589","https://openalex.org/W2760203759","https://openalex.org/W2765104835","https://openalex.org/W2952101609","https://openalex.org/W3111842353","https://openalex.org/W3180404591","https://openalex.org/W4220836744"],"related_works":["https://openalex.org/W2150702847","https://openalex.org/W2792528285","https://openalex.org/W4285175356","https://openalex.org/W4287165029","https://openalex.org/W2138825531","https://openalex.org/W2042246162","https://openalex.org/W2732433861","https://openalex.org/W2057568930","https://openalex.org/W4317770425","https://openalex.org/W1980634671"],"abstract_inverted_index":{"Coprime":[0],"arrays":[1],"are":[2],"able":[3],"to":[4,8,13,86,101],"utilize":[5],"two":[6,68],"subarrays":[7],"construct":[9],"a":[10,42,110],"difference":[11],"coarray":[12],"obtain":[14,87,122],"more":[15],"degrees":[16,96],"of":[17,67,97,139],"freedom":[18,98],"(DOF).":[19],"A":[20],"novel":[21],"frequency":[22],"diverse":[23],"coprime":[24],"array":[25],"(FDCA)":[26],"is":[27,48,65],"developed":[28,144],"for":[29,33],"estimating":[30],"the":[31,52,60,137,143],"angle-range":[32,45],"FDA-multiple":[34],"input":[35],"multiple":[36,113],"output":[37],"(MIMO)":[38],"radar.":[39],"In":[40,105],"addition,":[41],"tensor-based":[43,111],"joint":[44],"estimation":[46,125],"algorithm":[47],"developed,":[49],"which":[50,71,118],"avoids":[51],"2-dimensional":[53],"spectral":[54],"peak":[55],"searching":[56],"and":[57,142],"substantially":[58],"reduces":[59],"computational":[61],"complexity.":[62],"The":[63],"FDCA":[64],"composed":[66],"FDA":[69],"subarrays,":[70],"requires":[72,131],"only":[73,120],"<Formula":[74,88],"format=\"inline\"><TexMath><?TeX":[75,89],"$O\\{":[76,90],"M":[77],"+":[78],"N\\}":[79],"$":[80,92],"?></TexMath><File":[81,93],"name=\"a00--inline1\"":[82],"type=\"gif\"/></Formula>":[83,95],"physical":[84],"antennas":[85],"MN\\}":[91],"name=\"a00--inline2\"":[94],"(DOFs)":[99],"compared":[100],"conventional":[102],"FDA-MIMO":[103],"radars.":[104],"this":[106],"paper,":[107],"we":[108],"propose":[109],"reduced-dimension":[112],"signal":[114],"classification":[115],"(RD-MUSIC)":[116],"algorithm,":[117],"not":[119],"can":[121],"accurate":[123],"parameter":[124],"in":[126],"FDCA-MIMO":[127,140],"radar,":[128],"but":[129],"also":[130],"low":[132],"computation.":[133],"Simulation":[134],"experiments":[135],"verify":[136],"advantages":[138],"radar":[141],"algorithm.":[145]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
