{"id":"https://openalex.org/W4313362481","doi":"https://doi.org/10.3390/rs15010185","title":"CAE-CNN-Based DOA Estimation Method for Low-Elevation-Angle Target","display_name":"CAE-CNN-Based DOA Estimation Method for Low-Elevation-Angle Target","publication_year":2022,"publication_date":"2022-12-29","ids":{"openalex":"https://openalex.org/W4313362481","doi":"https://doi.org/10.3390/rs15010185"},"language":"en","primary_location":{"id":"doi:10.3390/rs15010185","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15010185","pdf_url":"https://www.mdpi.com/2072-4292/15/1/185/pdf?version=1672309824","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/1/185/pdf?version=1672309824","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034962692","display_name":"Fangzheng Zhao","orcid":"https://orcid.org/0000-0003-0421-5917"},"institutions":[{"id":"https://openalex.org/I4210104252","display_name":"Air Force Engineering University","ror":"https://ror.org/00seraz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210104252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fangzheng Zhao","raw_affiliation_strings":["Graduate School, Air Force Engineering University, Xi\u2019an 710043, China","Graduate School, Air Force Engineering University, Xi'an 710043, China"],"affiliations":[{"raw_affiliation_string":"Graduate School, Air Force Engineering University, Xi\u2019an 710043, China","institution_ids":["https://openalex.org/I4210104252"]},{"raw_affiliation_string":"Graduate School, Air Force Engineering University, Xi'an 710043, China","institution_ids":["https://openalex.org/I4210104252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076447478","display_name":"Guoping Hu","orcid":"https://orcid.org/0000-0002-7939-4588"},"institutions":[{"id":"https://openalex.org/I4210104252","display_name":"Air Force Engineering University","ror":"https://ror.org/00seraz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210104252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoping Hu","raw_affiliation_strings":["Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710043, China","Air and Missile Defense College, Air Force Engineering University, Xi'an 710043, China"],"affiliations":[{"raw_affiliation_string":"Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710043, China","institution_ids":["https://openalex.org/I4210104252"]},{"raw_affiliation_string":"Air and Missile Defense College, Air Force Engineering University, Xi'an 710043, China","institution_ids":["https://openalex.org/I4210104252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083044419","display_name":"Hao Zhou","orcid":"https://orcid.org/0000-0002-5284-7321"},"institutions":[{"id":"https://openalex.org/I4210104252","display_name":"Air Force Engineering University","ror":"https://ror.org/00seraz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210104252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhou","raw_affiliation_strings":["Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710043, China","Air and Missile Defense College, Air Force Engineering University, Xi'an 710043, China"],"affiliations":[{"raw_affiliation_string":"Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710043, China","institution_ids":["https://openalex.org/I4210104252"]},{"raw_affiliation_string":"Air and Missile Defense College, Air Force Engineering University, Xi'an 710043, China","institution_ids":["https://openalex.org/I4210104252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080132314","display_name":"Chenghong Zhan","orcid":"https://orcid.org/0000-0002-9160-3872"},"institutions":[{"id":"https://openalex.org/I4210104252","display_name":"Air Force Engineering University","ror":"https://ror.org/00seraz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210104252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenghong Zhan","raw_affiliation_strings":["Graduate School, Air Force Engineering University, Xi\u2019an 710043, China","Graduate School, Air Force Engineering University, Xi'an 710043, China"],"affiliations":[{"raw_affiliation_string":"Graduate School, Air Force Engineering University, Xi\u2019an 710043, China","institution_ids":["https://openalex.org/I4210104252"]},{"raw_affiliation_string":"Graduate School, Air Force Engineering University, Xi'an 710043, China","institution_ids":["https://openalex.org/I4210104252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5034962692"],"corresponding_institution_ids":["https://openalex.org/I4210104252"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.4458,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60289904,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"15","issue":"1","first_page":"185","last_page":"185"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9994999766349792,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9987000226974487,"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/T11698","display_name":"Underwater Acoustics Research","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9115891456604004},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7871606349945068},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7199273705482483},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6874609589576721},{"id":"https://openalex.org/keywords/multipath-propagation","display_name":"Multipath propagation","score":0.6018360257148743},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5612983703613281},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5059451460838318},{"id":"https://openalex.org/keywords/direction-of-arrival","display_name":"Direction of arrival","score":0.4854636788368225},{"id":"https://openalex.org/keywords/convolutional-code","display_name":"Convolutional code","score":0.4675534963607788},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46741533279418945},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.33511728048324585},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19623544812202454},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11059296131134033}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9115891456604004},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7871606349945068},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7199273705482483},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6874609589576721},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.6018360257148743},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5612983703613281},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5059451460838318},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.4854636788368225},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.4675534963607788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46741533279418945},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33511728048324585},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19623544812202454},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11059296131134033},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0},{"id":"https://openalex.org/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15010185","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15010185","pdf_url":"https://www.mdpi.com/2072-4292/15/1/185/pdf?version=1672309824","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d8554f40570b471eb59d3b6ccffb8743","is_oa":true,"landing_page_url":"https://doaj.org/article/d8554f40570b471eb59d3b6ccffb8743","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 1, p 185 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/1/185/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15010185","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 15; Issue 1; Pages: 185","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15010185","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15010185","pdf_url":"https://www.mdpi.com/2072-4292/15/1/185/pdf?version=1672309824","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2349868059","display_name":null,"funder_award_id":"6207011332","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":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4313362481.pdf","grobid_xml":"https://content.openalex.org/works/W4313362481.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1972084306","https://openalex.org/W1986363767","https://openalex.org/W1994477821","https://openalex.org/W2109683057","https://openalex.org/W2136274821","https://openalex.org/W2319450735","https://openalex.org/W2504751434","https://openalex.org/W2547086878","https://openalex.org/W2741871412","https://openalex.org/W2897361856","https://openalex.org/W2940696759","https://openalex.org/W2979390797","https://openalex.org/W3009340533","https://openalex.org/W3009691008","https://openalex.org/W3163367709","https://openalex.org/W3213850418","https://openalex.org/W3215055741","https://openalex.org/W3216582455","https://openalex.org/W4205488300","https://openalex.org/W4211136489","https://openalex.org/W4302029350","https://openalex.org/W6845867499"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4289763776","https://openalex.org/W2810330923"],"abstract_inverted_index":{"For":[0],"the":[1,12,39,44,47,56,61,65,70,74,77,83,91,97,106,109,115,129,138,143,146,150,156,161,167,173,176],"DOA":[2,22,84,122,144,190],"(direction":[3],"of":[4,7,14,43,46,76,86,96,108,117,145,155,178],"arrival)":[5],"estimation":[6,23,133,191],"a":[8,15,21],"low-elevation-angle":[9],"target":[10,49,147],"under":[11],"influence":[13],"multipath":[16],"effect,":[17],"this":[18,118],"paper":[19],"proposes":[20],"method":[24],"based":[25,89],"on":[26,90],"CAE":[27],"(convolutional":[28,32],"autoencoder)":[29],"and":[30,52,63,105,135,175,186,188],"CNN":[31],"neural":[33,101,181],"network).":[34],"The":[35,124,153],"algorithm":[36,130,162],"firstly":[37],"inputs":[38],"signal":[40],"covariance":[41],"matrix":[42],"array":[45],"low-elevation":[48],"containing":[50],"direct":[51,87],"reflected":[53],"waves":[54],"into":[55],"convolutional":[57,71,100,110,168,180],"autoencoder":[58,72,111,169],"to":[59,81,120],"realize":[60,82,121,172,189],"de-multipath,":[62,174],"uses":[64],"spatial":[66],"features":[67],"extracted":[68],"by":[69],"as":[73,114],"input":[75,116],"extreme":[78],"learning":[79],"machine":[80],"preclassification":[85,92],"waves;":[88],"results,":[93],"one":[94],"branch":[95,119],"three":[98],"parallel":[99,179],"nets":[102],"is":[103,112,148,163],"selected,":[104],"output":[107],"used":[113],"estimation.":[123],"simulation":[125,157],"results":[126,158],"show":[127],"that":[128,160],"has":[131],"better":[132],"accuracy":[134],"efficiency":[136],"than":[137],"conventional":[139],"algorithms,":[140],"especially":[141],"when":[142],"in":[149,165],"lower":[151],"range.":[152],"analysis":[154],"shows":[159],"effective,":[164],"which":[166],"can":[170,183],"effectively":[171],"use":[177],"networks":[182],"avoid":[184],"overfitting":[185],"underfitting":[187],"more":[192],"accurately.":[193]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
