{"id":"https://openalex.org/W1840522340","doi":"https://doi.org/10.1109/tsp.2014.2323022","title":"Radar Target Profiling and Recognition Based on TSI-Optimized Compressive Sensing Kernel","display_name":"Radar Target Profiling and Recognition Based on TSI-Optimized Compressive Sensing Kernel","publication_year":2014,"publication_date":"2014-05-22","ids":{"openalex":"https://openalex.org/W1840522340","doi":"https://doi.org/10.1109/tsp.2014.2323022","mag":"1840522340"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2014.2323022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2014.2323022","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","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/A5015909551","display_name":"Yujie Gu","orcid":"https://orcid.org/0000-0003-1312-1605"},"institutions":[{"id":"https://openalex.org/I4210145244","display_name":"Radar (United States)","ror":"https://ror.org/05c5a2504","country_code":"US","type":"company","lineage":["https://openalex.org/I4210145244"]},{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yujie Gu","raw_affiliation_strings":["School of Electrical and Computer Engineering, Advanced Radar Research Center The University of Oklahoma, Norman, OK, USA","School of Electrical and Computer Engineering, Advanced Radar Research Center, The University of Oklahoma, Norman, OK, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Advanced Radar Research Center The University of Oklahoma, Norman, OK, USA","institution_ids":["https://openalex.org/I8692664","https://openalex.org/I4210145244"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, Advanced Radar Research Center, The University of Oklahoma, Norman, OK, USA#TAB#","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008913364","display_name":"Nathan A. Goodman","orcid":"https://orcid.org/0000-0002-7939-1395"},"institutions":[{"id":"https://openalex.org/I4210145244","display_name":"Radar (United States)","ror":"https://ror.org/05c5a2504","country_code":"US","type":"company","lineage":["https://openalex.org/I4210145244"]},{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nathan A. Goodman","raw_affiliation_strings":["School of Electrical and Computer Engineering The University of Oklahoma, Norman, OK, USA","Advanced Radar Research Center, The University of Oklahoma, Norman, OK, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering The University of Oklahoma, Norman, OK, USA","institution_ids":["https://openalex.org/I8692664"]},{"raw_affiliation_string":"Advanced Radar Research Center, The University of Oklahoma, Norman, OK, USA","institution_ids":["https://openalex.org/I8692664","https://openalex.org/I4210145244"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033025873","display_name":"Amit Ashok","orcid":"https://orcid.org/0000-0002-1108-2481"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]},{"id":"https://openalex.org/I4210122332","display_name":"Optical Sciences (United States)","ror":"https://ror.org/03122yk49","country_code":"US","type":"company","lineage":["https://openalex.org/I4210122332"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amit Ashok","raw_affiliation_strings":["College of Optical Science, The University of Arizona, Tucson, AZ, USA","[College of Optical Science, The University of Arizona, Tucson, AZ, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Optical Science, The University of Arizona, Tucson, AZ, USA","institution_ids":["https://openalex.org/I4210122332","https://openalex.org/I138006243"]},{"raw_affiliation_string":"[College of Optical Science, The University of Arizona, Tucson, AZ, USA]","institution_ids":["https://openalex.org/I138006243"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.4745,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.95704327,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"62","issue":"12","first_page":"3194","last_page":"3207"},"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":0.9994999766349792,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6921711564064026},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6653075814247131},{"id":"https://openalex.org/keywords/nyquist-rate","display_name":"Nyquist rate","score":0.6275604963302612},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5865017771720886},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.4662230312824249},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.439456045627594},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4363567531108856},{"id":"https://openalex.org/keywords/wideband","display_name":"Wideband","score":0.41099175810813904},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38596010208129883},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35485631227493286},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.30725574493408203},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.258773535490036},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22560015320777893},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.20237404108047485},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15815454721450806},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1258051097393036}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6921711564064026},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6653075814247131},{"id":"https://openalex.org/C65914096","wikidata":"https://www.wikidata.org/wiki/Q6273772","display_name":"Nyquist rate","level":4,"score":0.6275604963302612},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5865017771720886},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.4662230312824249},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.439456045627594},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4363567531108856},{"id":"https://openalex.org/C2780202535","wikidata":"https://www.wikidata.org/wiki/Q4524457","display_name":"Wideband","level":2,"score":0.41099175810813904},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38596010208129883},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35485631227493286},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.30725574493408203},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.258773535490036},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22560015320777893},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.20237404108047485},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15815454721450806},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1258051097393036},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2014.2323022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2014.2323022","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8299999833106995,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G3300110954","display_name":null,"funder_award_id":"#N66001-10-1-4079","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W250076511","https://openalex.org/W1967662829","https://openalex.org/W1989264550","https://openalex.org/W1998374792","https://openalex.org/W2022265006","https://openalex.org/W2057069782","https://openalex.org/W2069667906","https://openalex.org/W2076550855","https://openalex.org/W2091256848","https://openalex.org/W2109320267","https://openalex.org/W2111616148","https://openalex.org/W2122548617","https://openalex.org/W2124712881","https://openalex.org/W2125680629","https://openalex.org/W2129638195","https://openalex.org/W2134929491","https://openalex.org/W2135859872","https://openalex.org/W2141426461","https://openalex.org/W2147276092","https://openalex.org/W2153642672","https://openalex.org/W2157589572","https://openalex.org/W2160978899","https://openalex.org/W2167404137","https://openalex.org/W2296616510","https://openalex.org/W2478708596","https://openalex.org/W3101339175","https://openalex.org/W3125735862","https://openalex.org/W4250589301","https://openalex.org/W4250955649","https://openalex.org/W6673172288"],"related_works":["https://openalex.org/W4200358983","https://openalex.org/W1483997978","https://openalex.org/W2611619770","https://openalex.org/W2889294138","https://openalex.org/W4250067459","https://openalex.org/W2786561765","https://openalex.org/W2393783098","https://openalex.org/W2005032074","https://openalex.org/W2356275480","https://openalex.org/W2520516827"],"abstract_inverted_index":{"The":[0,132,146],"design":[1,69,174,200],"of":[2,22,56,58,92,111,114,124,169],"wideband":[3],"radar":[4,34,89],"systems":[5],"is":[6,38,148],"often":[7],"limited":[8],"by":[9],"existing":[10],"analog-to-digital":[11],"(A/D)":[12],"converter":[13],"technology.":[14],"State-of-the-art":[15],"A/D":[16],"rates":[17],"and":[18,29,50,66,105,143,178],"high":[19],"effective":[20],"number":[21],"bits":[23],"result":[24],"in":[25,51,151],"rapidly":[26],"increasing":[27],"cost":[28],"power":[30],"consumption":[31],"for":[32,87,102,157,197],"the":[33,103,112,115,129,158,167,170,187,194],"system.":[35],"Therefore,":[36],"it":[37],"useful":[39],"to":[40,68,83,119,128,155,175,179],"consider":[41],"compressive":[42,71],"sensing":[43,85,130,160,172,198],"methods":[44],"that":[45,182,193],"enable":[46,120],"reduced":[47],"sampling":[48],"rate,":[49],"many":[52],"applications,":[53],"prior":[54],"knowledge":[55],"signals":[57],"interest":[59],"can":[60,183,201],"be":[61,184],"learned":[62],"from":[63],"training":[64],"data":[65],"used":[67,150],"better":[70],"measurement":[72],"kernels.":[73],"In":[74,162],"this":[75],"paper,":[76],"we":[77,165],"use":[78,106],"a":[79,97,107,121,152],"task-specific":[80],"information-based":[81],"approach":[82,154],"optimizing":[84],"kernels":[86],"highresolution":[88],"range":[90,144],"profiling":[91],"man-made":[93],"targets.":[94],"We":[95],"employ":[96],"Gaussian":[98],"mixture":[99],"(GM)":[100],"model":[101,134],"targets":[104],"Taylor":[108],"series":[109],"expansion":[110],"logarithm":[113],"GM":[116,133],"probability":[117],"distribution":[118],"closed-form":[122],"gradient":[123,147],"information":[125],"with":[126],"respect":[127],"kernel.":[131,161],"admits":[135],"nuisance":[136],"parameters":[137],"such":[138],"as":[139],"target":[140],"pose":[141],"angle":[142],"translation.":[145],"then":[149],"gradient-based":[153],"search":[156],"optimal":[159],"numerical":[163],"simulations,":[164],"compare":[166],"performance":[168],"proposed":[171,195],"kernel":[173,199],"random":[176],"projections":[177],"lower-bandwidth":[180],"waveforms":[181],"sampled":[185],"at":[186],"Nyquist":[188],"rate.":[189],"Simulation":[190],"results":[191],"demonstrate":[192],"technique":[196],"significantly":[202],"improve":[203],"performance.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
