{"id":"https://openalex.org/W4382998821","doi":"https://doi.org/10.1109/tgrs.2023.3291873","title":"High-Resolution ISAR Imaging With SSFCS Based on Nonparametric Bayesian Learning and Genetic Algorithm","display_name":"High-Resolution ISAR Imaging With SSFCS Based on Nonparametric Bayesian Learning and Genetic Algorithm","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4382998821","doi":"https://doi.org/10.1109/tgrs.2023.3291873"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3291873","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3291873","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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/A5100646924","display_name":"Yue Wang","orcid":"https://orcid.org/0009-0005-0902-3107"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yue Wang","raw_affiliation_strings":["National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103221264","display_name":"Z. Yujie","orcid":"https://orcid.org/0000-0003-1392-3069"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujie Zhang","raw_affiliation_strings":["National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076901636","display_name":"Xueru Bai","orcid":"https://orcid.org/0000-0001-9283-1810"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueru Bai","raw_affiliation_strings":["National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100646924"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":13.1364,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.98244506,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9997000098228455,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9997000098228455,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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":0.7265743613243103},{"id":"https://openalex.org/keywords/inverse-synthetic-aperture-radar","display_name":"Inverse synthetic aperture radar","score":0.7090907096862793},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.563839316368103},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5460720658302307},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5314900875091553},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.5119770765304565},{"id":"https://openalex.org/keywords/image-formation","display_name":"Image formation","score":0.4824717342853546},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.47268468141555786},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4325045645236969},{"id":"https://openalex.org/keywords/motion-compensation","display_name":"Motion compensation","score":0.427140474319458},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4095267951488495},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.35710036754608154},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.2995782494544983},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22699874639511108}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7265743613243103},{"id":"https://openalex.org/C109094680","wikidata":"https://www.wikidata.org/wiki/Q6060432","display_name":"Inverse synthetic aperture radar","level":4,"score":0.7090907096862793},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.563839316368103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5460720658302307},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5314900875091553},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.5119770765304565},{"id":"https://openalex.org/C125045340","wikidata":"https://www.wikidata.org/wiki/Q6002224","display_name":"Image formation","level":3,"score":0.4824717342853546},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.47268468141555786},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4325045645236969},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.427140474319458},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4095267951488495},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.35710036754608154},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.2995782494544983},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22699874639511108},{"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/tgrs.2023.3291873","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3291873","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2630173159","display_name":null,"funder_award_id":"61971332","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3937783750","display_name":null,"funder_award_id":"62131020","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"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1985885848","https://openalex.org/W1993357967","https://openalex.org/W2000721204","https://openalex.org/W2013352441","https://openalex.org/W2019806702","https://openalex.org/W2037751135","https://openalex.org/W2044663059","https://openalex.org/W2073682504","https://openalex.org/W2101800734","https://openalex.org/W2118052063","https://openalex.org/W2124562418","https://openalex.org/W2131084851","https://openalex.org/W2143060757","https://openalex.org/W2152176246","https://openalex.org/W2737805599","https://openalex.org/W2737840656","https://openalex.org/W2763296532","https://openalex.org/W2801349651","https://openalex.org/W2885676805","https://openalex.org/W2889774027","https://openalex.org/W2974318786","https://openalex.org/W2990044891","https://openalex.org/W2995445161","https://openalex.org/W2999857168","https://openalex.org/W3011852478","https://openalex.org/W3013242743","https://openalex.org/W3037793751","https://openalex.org/W3040121955","https://openalex.org/W3080452742","https://openalex.org/W3126451592","https://openalex.org/W3167611188","https://openalex.org/W3202807108","https://openalex.org/W3210904994","https://openalex.org/W4210930491","https://openalex.org/W4213423178","https://openalex.org/W4225484399","https://openalex.org/W4232023503","https://openalex.org/W4293191880","https://openalex.org/W4312940983","https://openalex.org/W4319585979","https://openalex.org/W6753883431"],"related_works":["https://openalex.org/W2119869625","https://openalex.org/W2354389511","https://openalex.org/W2140944036","https://openalex.org/W2007886977","https://openalex.org/W2350566760","https://openalex.org/W1777074644","https://openalex.org/W2128890580","https://openalex.org/W1530257205","https://openalex.org/W2143414251","https://openalex.org/W2147173157"],"abstract_inverted_index":{"For":[0],"inverse":[1],"synthetic":[2],"aperture":[3],"radar":[4],"(ISAR)":[5],"adopting":[6],"the":[7,14,20,61,75,99,121,125,137,140],"sparse":[8,18],"stepped":[9],"frequency":[10],"chirp":[11],"signal":[12,62],"(SSFCS),":[13],"target":[15],"echoes":[16],"are":[17],"in":[19],"fast":[21],"time":[22],"domain":[23],"with":[24,74],"unknown":[25],"phase":[26],"errors":[27],"induced":[28],"by":[29,97],"translational":[30,122],"motion,":[31],"bringing":[32],"great":[33],"challenges":[34],"to":[35,70,118],"well-focused":[36],"imaging.":[37],"To":[38],"tackle":[39],"this":[40],"issue,":[41],"an":[42],"efficient":[43,90],"method":[44],"for":[45,89],"joint":[46],"motion":[47,123],"compensation":[48],"and":[49,102,113,124,132],"high-resolution":[50],"imaging":[51],"is":[52,64,67,87,111,116],"proposed":[53,88,141],"under":[54],"low":[55],"signal-to-noise":[56],"ratio":[57],"(SNR)":[58],"scenario.":[59],"Firstly,":[60],"model":[63,73],"constructed,":[65],"which":[66,93],"then":[68],"converted":[69],"a":[71,108],"probabilistic":[72],"nonparametric":[76],"Gamma":[77],"Process-Complex":[78],"Gaussian":[79],"prior.":[80],"Then,":[81],"2D-fast":[82],"image":[83,91],"reconstruction,":[84],"i.e.,":[85],"2D-FIR,":[86],"inference,":[92],"avoids":[94],"matrix":[95],"inversion":[96],"relaxing":[98],"lower":[100],"bound":[101],"has":[103],"high":[104],"computational":[105],"efficiency.":[106],"Finally,":[107],"cost":[109],"function":[110],"designed":[112],"genetic":[114],"algorithm":[115],"utilized":[117],"jointly":[119],"estimate":[120],"2D":[126],"image.":[127],"Experimental":[128],"results":[129],"on":[130],"simulated":[131],"measured":[133],"data":[134],"have":[135],"verified":[136],"effectiveness":[138],"of":[139],"method.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-05T09:29:38.588285","created_date":"2025-10-10T00:00:00"}