{"id":"https://openalex.org/W2122781885","doi":"https://doi.org/10.1109/igarss.2011.6049989","title":"Robust recovery of synthetic aperture radar data from uniformly under-sampled measurements","display_name":"Robust recovery of synthetic aperture radar data from uniformly under-sampled measurements","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2122781885","doi":"https://doi.org/10.1109/igarss.2011.6049989","mag":"2122781885"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2011.6049989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2011.6049989","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Geoscience and Remote Sensing Symposium","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/A5032510248","display_name":"Lam Nguyen","orcid":"https://orcid.org/0000-0003-3347-4379"},"institutions":[{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lam H. Nguyen","raw_affiliation_strings":["U.S. Army Research Laboratory, Adelphi, MD, USA","U.S. Army Research Laboratory , Adelphi, MD, 20783, USA"],"affiliations":[{"raw_affiliation_string":"U.S. Army Research Laboratory, Adelphi, MD, USA","institution_ids":["https://openalex.org/I166416128"]},{"raw_affiliation_string":"U.S. Army Research Laboratory , Adelphi, MD, 20783, USA","institution_ids":["https://openalex.org/I166416128"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101413113","display_name":"Trac D. Tran","orcid":"https://orcid.org/0000-0002-0421-8416"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Trac D. Tran","raw_affiliation_strings":["Johns Hopkins University, Baltimore, MD, USA","The Johns Hopkins University, Baltimore, MD 21218 USA"],"affiliations":[{"raw_affiliation_string":"Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"The Johns Hopkins University, Baltimore, MD 21218 USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5032510248"],"corresponding_institution_ids":["https://openalex.org/I166416128"],"apc_list":null,"apc_paid":null,"fwci":1.7226,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.84509228,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"6561","issue":null,"first_page":"3554","last_page":"3557"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":0.9995999932289124,"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"}},{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9993000030517578,"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/computer-science","display_name":"Computer science","score":0.7215010523796082},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6769386529922485},{"id":"https://openalex.org/keywords/inverse-synthetic-aperture-radar","display_name":"Inverse synthetic aperture radar","score":0.6083059310913086},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5990875363349915},{"id":"https://openalex.org/keywords/nyquist-rate","display_name":"Nyquist rate","score":0.5976684093475342},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.546289324760437},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.5388469696044922},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5107421875},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.5058484077453613},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49326032400131226},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.48119527101516724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.470255970954895},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.4208610951900482},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.4170289635658264},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4010251462459564},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.2515608072280884},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.21510154008865356},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.19950774312019348},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14830082654953003},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12605562806129456}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7215010523796082},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6769386529922485},{"id":"https://openalex.org/C109094680","wikidata":"https://www.wikidata.org/wiki/Q6060432","display_name":"Inverse synthetic aperture radar","level":4,"score":0.6083059310913086},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5990875363349915},{"id":"https://openalex.org/C65914096","wikidata":"https://www.wikidata.org/wiki/Q6273772","display_name":"Nyquist rate","level":4,"score":0.5976684093475342},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.546289324760437},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.5388469696044922},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5107421875},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.5058484077453613},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49326032400131226},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.48119527101516724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.470255970954895},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.4208610951900482},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.4170289635658264},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4010251462459564},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2515608072280884},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.21510154008865356},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.19950774312019348},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14830082654953003},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12605562806129456}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2011.6049989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2011.6049989","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2023722580","https://openalex.org/W2032803057","https://openalex.org/W2119667497","https://openalex.org/W2127271355","https://openalex.org/W2129638195","https://openalex.org/W2145096794","https://openalex.org/W2244062808","https://openalex.org/W2296616510","https://openalex.org/W3124114587","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W2378166785","https://openalex.org/W2382972663","https://openalex.org/W2388133936","https://openalex.org/W2023352781","https://openalex.org/W2465351041","https://openalex.org/W1555738523","https://openalex.org/W2103001330","https://openalex.org/W2946877649","https://openalex.org/W2340242818","https://openalex.org/W4200575023"],"abstract_inverted_index":{"In":[0,67],"this":[1],"paper,":[2],"we":[3,41,111],"propose":[4],"a":[5,54,84,143,170],"novel":[6],"robust":[7],"sparse-recovery":[8,116],"technique":[9,72,120,157],"that":[10,43,113,137],"allows":[11],"sub-Nyquist":[12,216],"uniform":[13],"under-sampling":[14],"of":[15,26,56,91,145,164,204],"wide-bandwidth":[16],"radar":[17,47,109,127],"data":[18,48,97,128,159],"in":[19,31,64,207],"real":[20],"time":[21],"(single":[22],"observation).":[23],"Although":[24],"much":[25],"the":[27,32,37,65,92,99,114,125,139,150,155,165,176,183,195,214],"information":[28],"is":[29,73],"lost":[30],"received":[33],"signal":[34,141],"due":[35],"to":[36,175],"low":[38],"sampling":[39,167,217],"rate,":[40],"hypothesize":[42],"each":[44],"wide-":[45],"bandwidth":[46],"record":[49],"can":[50],"be":[51],"modeled":[52],"as":[53],"superposition":[55],"many":[57,88],"backscattered":[58],"signals":[59],"from":[60,98,129,190],"reflective":[61],"point":[62],"targets":[63],"scene.":[66],"other":[68],"words,":[69],"our":[70],"proposed":[71,115],"based":[74,118,199],"on":[75],"direct":[76],"sparse":[77],"recovery":[78],"via":[79],"orthogonal":[80],"matching":[81],"pursuit":[82],"using":[83,132,154],"special":[85],"dictionary":[86],"containing":[87],"time-delayed":[89],"versions":[90],"transmitted":[93,140],"probing":[94],"signal.":[95],"Using":[96],"U.S.":[100],"Army":[101],"Research":[102],"Laboratory":[103],"(ARL)":[104],"Ultra-Wideband":[105],"(UWB)":[106],"synthetic":[107],"aperture":[108],"(SAR),":[110],"show":[112],"model-":[117],"(SMB)":[119],"successfully":[121],"models":[122,138],"and":[123,142,194],"synthesizes":[124],"returned":[126],"real-world":[130],"scenes":[131],"only":[133,162],"an":[134],"analytical":[135],"waveform":[136],"handful":[144],"reflectivity":[146],"coefficients.":[147],"More":[148],"importantly,":[149],"reconstructed":[151],"SAR":[152,178,187,210],"imagery":[153],"SBM":[156],"with":[158],"sampled":[160],"at":[161,213],"20%":[163],"original":[166,177],"rate":[168,218],"has":[169],"comparable":[171],"signal-to-noise":[172],"ratio":[173],"(SNR)":[174],"imagery.":[179],"For":[180],"comparison":[181],"purpose,":[182],"paper":[184],"also":[185],"presents":[186],"images":[188],"recovered":[189],"conventional":[191],"interpolation":[192],"techniques":[193],"standard":[196],"random":[197],"projection":[198],"compressed":[200],"sensing":[201],"technique,":[202],"both":[203],"which":[205],"resulted":[206],"very":[208],"poor":[209],"image":[211],"quality":[212],"same":[215],"(20%).":[219]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
