{"id":"https://openalex.org/W3134037552","doi":"https://doi.org/10.1109/iws49314.2020.9360020","title":"Weighted L1-Norm for One-Bit Compressed Sensing Based on Approximated Observation","display_name":"Weighted L1-Norm for One-Bit Compressed Sensing Based on Approximated Observation","publication_year":2020,"publication_date":"2020-09-20","ids":{"openalex":"https://openalex.org/W3134037552","doi":"https://doi.org/10.1109/iws49314.2020.9360020","mag":"3134037552"},"language":"en","primary_location":{"id":"doi:10.1109/iws49314.2020.9360020","doi":"https://doi.org/10.1109/iws49314.2020.9360020","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iws49314.2020.9360020","pdf_url":null,"source":{"id":"https://openalex.org/S4363605414","display_name":"IEEE MTT-S International Wireless Symposium (IWS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE MTT-S International Wireless Symposium (IWS)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5100401037","display_name":"Zheng Wang","orcid":"https://orcid.org/0000-0001-5330-4532","observed_orcids":["https://orcid.org/0000-0001-5330-4532"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Wang","raw_affiliation_strings":["Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046052004","display_name":"Falin Liu","orcid":"https://orcid.org/0000-0001-6815-7133","observed_orcids":["https://orcid.org/0000-0001-6815-7133"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Falin Liu","raw_affiliation_strings":["Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102443185","display_name":"Yanwei Yin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanwei Yin","raw_affiliation_strings":["Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100758169","display_name":"Bo Hu Li","orcid":"https://orcid.org/0000-0001-5980-4861","observed_orcids":["https://orcid.org/0000-0001-5980-4861"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Li","raw_affiliation_strings":["Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091744102","display_name":"Yuanyue Guo","orcid":"https://orcid.org/0000-0003-1697-7329","observed_orcids":["https://orcid.org/0000-0003-1697-7329"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyue Guo","raw_affiliation_strings":["Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":0.7373,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.71305053,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.5356000065803528,"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":0.5356000065803528,"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":0.4546000063419342,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.0032999999821186066,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/one-bit-compressed-sensing","display_name":"one-bit compressed sensing","score":0.996999979019165},{"id":"https://openalex.org/keywords/sar-imaging","display_name":"synthetic aperture radar imaging","score":0.972000002861023},{"id":"https://openalex.org/keywords/sub-nyquist-sampling","display_name":"sub-Nyquist sampling","score":0.8790000081062317},{"id":"https://openalex.org/keywords/computational-cost-reduction","display_name":"computational complexity reduction","score":0.6119999885559082},{"id":"https://openalex.org/keywords/high-resolution-imaging","display_name":"high-resolution imaging","score":0.5289999842643738}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8231580257415771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7300068736076355},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.7102457284927368},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5866867899894714},{"id":"https://openalex.org/C65914096","wikidata":"https://www.wikidata.org/wiki/Q6273772","display_name":"Nyquist rate","level":4,"score":0.4851992428302765},{"id":"https://openalex.org/C109094680","wikidata":"https://www.wikidata.org/wiki/Q6060432","display_name":"Inverse synthetic aperture radar","level":4,"score":0.4817071557044983},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.4763907790184021},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.43856939673423767},{"id":"https://openalex.org/C288623","wikidata":"https://www.wikidata.org/wiki/Q679800","display_name":"Nyquist\u2013Shannon sampling theorem","level":2,"score":0.4280746281147003},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.37140756845474243},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33742567896842957},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.33188098669052124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33180320262908936},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.3009355664253235},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08580467104911804},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iws49314.2020.9360020","doi":"https://doi.org/10.1109/iws49314.2020.9360020","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iws49314.2020.9360020","pdf_url":null,"source":{"id":"https://openalex.org/S4363605414","display_name":"IEEE MTT-S International Wireless Symposium (IWS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE MTT-S International Wireless Symposium (IWS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G1595638021","display_name":null,"funder_award_id":"61431016,61771446","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1972801553","https://openalex.org/W2047042135","https://openalex.org/W2112038498","https://openalex.org/W2593772630","https://openalex.org/W4238744307"],"related_works":["https://openalex.org/W2509882771","https://openalex.org/W4416726391","https://openalex.org/W2047042135","https://openalex.org/W3006290722","https://openalex.org/W2885777122","https://openalex.org/W2036977160","https://openalex.org/W2953429301","https://openalex.org/W2994728251","https://openalex.org/W7152617737","https://openalex.org/W4384565012"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"one-bit":[3,71,139],"compressed":[4,72],"sensing":[5,32,73],"(CS)":[6],"has":[7],"been":[8],"applied":[9,101],"to":[10,102],"the":[11,31,42,87,94,113],"field":[12],"of":[13,30,96],"synthetic":[14],"aperture":[15],"radar":[16],"(SAR)":[17],"imaging":[18,77,106,136],"and":[19,62,104,120],"shows":[20],"great":[21],"potential.":[22],"The":[23],"existing":[24],"models":[25],"are,":[26],"based":[27,82],"on":[28,83],"application":[29],"matrix":[33],"acquired":[34],"by":[35],"exact":[36],"observation":[37,90],"functions.":[38],"As":[39],"a":[40,69,124],"result,":[41],"corresponding":[43],"reconstruction":[44],"algorithms":[45],"are":[46],"much":[47],"more":[48],"time":[49],"consuming":[50],"than":[51],"traditional":[52],"matched":[53],"filter":[54],"(MF)-based":[55],"focusing":[56],"methods,":[57],"especially":[58],"in":[59,118,123],"high":[60],"resolution":[61],"wide":[63],"swath":[64],"systems.":[65],"This":[66],"paper":[67],"presents":[68],"novel":[70],"approach":[74],"for":[75,142],"SAR":[76,89,135],"using":[78],"weighted":[79],"L1-Norm":[80],"Minimization":[81],"approximated":[84,88],"observation.It":[85],"adopts":[86],"model":[91],"deduced":[92],"from":[93],"inverse":[95],"MF-based":[97],"methods.It":[98],"can":[99,132],"be":[100],"high-quality":[103],"high-resolution":[105],"under":[107],"sub-Nyquist":[108],"rate":[109],"sampling,":[110],"while":[111],"decreasing":[112],"computational":[114],"cost":[115],"substantially":[116],"both":[117],"memory":[119],"time,":[121],"resulting":[122],"fast":[125],"approach.Simulations":[126],"results":[127],"show":[128],"that":[129],"our":[130],"method":[131],"perform":[133],"sparse":[134],"effectively":[137],"with":[138],"quantized":[140],"data":[141],"large":[143],"scale":[144],"applications.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-10-13T10:08:12.033832","created_date":"2021-03-15T00:00:00"}