{"id":"https://openalex.org/W4285287027","doi":"https://doi.org/10.1109/tsp.2022.3173477","title":"Inverse Beam Pattern Transform and Spatial Sampling for Uniform Array From Broadband Beamforming Perspective","display_name":"Inverse Beam Pattern Transform and Spatial Sampling for Uniform Array From Broadband Beamforming Perspective","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285287027","doi":"https://doi.org/10.1109/tsp.2022.3173477"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2022.3173477","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3173477","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/A5049333966","display_name":"Phan Le Son","orcid":null},"institutions":[{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Phan Le Son","raw_affiliation_strings":["Digitale Signalverarbeitung, Elektrotechnik und Infor- mationstechnik, Technische Universit&#x00E4;t Kaiserslautern, Kaiserslautern, Germany"],"affiliations":[{"raw_affiliation_string":"Digitale Signalverarbeitung, Elektrotechnik und Infor- mationstechnik, Technische Universit&#x00E4;t Kaiserslautern, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I153267046"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5049333966"],"corresponding_institution_ids":["https://openalex.org/I153267046"],"apc_list":null,"apc_paid":null,"fwci":0.6159,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.77998112,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"70","issue":null,"first_page":"2431","last_page":"2442"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11946","display_name":"Antenna Design and Optimization","score":0.9998000264167786,"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/T11946","display_name":"Antenna Design and Optimization","score":0.9998000264167786,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9997000098228455,"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/T10860","display_name":"Speech and Audio Processing","score":0.9991999864578247,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.7988336682319641},{"id":"https://openalex.org/keywords/aliasing","display_name":"Aliasing","score":0.5225776433944702},{"id":"https://openalex.org/keywords/nyquist\u2013shannon-sampling-theorem","display_name":"Nyquist\u2013Shannon sampling theorem","score":0.4886391758918762},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.4791490435600281},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4764026701450348},{"id":"https://openalex.org/keywords/sensor-array","display_name":"Sensor array","score":0.4691388010978699},{"id":"https://openalex.org/keywords/broadband","display_name":"Broadband","score":0.43400582671165466},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.42164346575737},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.4142984449863434},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4092542231082916},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.3688136637210846},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35018306970596313},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.3197695016860962},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.14941281080245972},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1427944004535675},{"id":"https://openalex.org/keywords/undersampling","display_name":"Undersampling","score":0.1314716935157776},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08738315105438232},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.07779455184936523}],"concepts":[{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.7988336682319641},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.5225776433944702},{"id":"https://openalex.org/C288623","wikidata":"https://www.wikidata.org/wiki/Q679800","display_name":"Nyquist\u2013Shannon sampling theorem","level":2,"score":0.4886391758918762},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.4791490435600281},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4764026701450348},{"id":"https://openalex.org/C66251956","wikidata":"https://www.wikidata.org/wiki/Q7451086","display_name":"Sensor array","level":2,"score":0.4691388010978699},{"id":"https://openalex.org/C509933004","wikidata":"https://www.wikidata.org/wiki/Q194163","display_name":"Broadband","level":2,"score":0.43400582671165466},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.42164346575737},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4142984449863434},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4092542231082916},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.3688136637210846},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35018306970596313},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.3197695016860962},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.14941281080245972},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1427944004535675},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.1314716935157776},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08738315105438232},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.07779455184936523},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2022.3173477","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3173477","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W52763984","https://openalex.org/W315971713","https://openalex.org/W636342949","https://openalex.org/W1593299244","https://openalex.org/W1898225171","https://openalex.org/W1967895044","https://openalex.org/W1994749532","https://openalex.org/W1997024121","https://openalex.org/W2011447765","https://openalex.org/W2015580348","https://openalex.org/W2026126889","https://openalex.org/W2041825099","https://openalex.org/W2049100819","https://openalex.org/W2060108923","https://openalex.org/W2069935093","https://openalex.org/W2081472029","https://openalex.org/W2095296829","https://openalex.org/W2164710420","https://openalex.org/W3023885642","https://openalex.org/W3108273125","https://openalex.org/W4200382728","https://openalex.org/W4249459349","https://openalex.org/W4252713891"],"related_works":["https://openalex.org/W2067196003","https://openalex.org/W1970456080","https://openalex.org/W2176079168","https://openalex.org/W2367359316","https://openalex.org/W3206156900","https://openalex.org/W2119250743","https://openalex.org/W1997066351","https://openalex.org/W4232991790","https://openalex.org/W2283343509","https://openalex.org/W4384499572"],"abstract_inverted_index":{"A":[0],"sensor":[1,67],"array":[2,45,164],"collects":[3],"spatial":[4,14,103],"samples":[5],"of":[6,34,48,102,107,115,119,126],"propagating":[7],"wave":[8],"fields,":[9],"and":[10,25,69,95,130,140],"a":[11,37,43,60],"beamformer":[12],"performs":[13],"filtering":[15],"to":[16,53,160],"preserve":[17],"the":[18,32,49,63,66,92,100,105,108,116,120,124,127,137,144,149,153,162],"desired":[19],"signal":[20,38],"while":[21],"suppressing":[22],"interfering":[23],"signals":[24],"noise":[26],"arriving":[27],"from":[28,123],"directions":[29],"other":[30,138],"than":[31,113],"direction":[33],"interest.":[35],"Given":[36],"with":[39,165],"wideband":[40],"frequency,":[41],"using":[42],"uniform":[44,163],"is":[46,75,79,152],"one":[47],"most":[50],"common":[51],"approaches":[52],"obtain":[54],"broadband":[55,131,166],"beamforming.":[56,167],"In":[57],"this":[58,134],"work,":[59],"function":[61,78,129,151,155],"formulating":[62],"relations":[64],"between":[65],"coefficients":[68],"its":[70],"beam":[71,82,87],"pattern":[72,83,88],"over":[73],"frequency":[74],"introduced.":[76],"The":[77,85],"called":[80],"inverse":[81,86,96],"transform.":[84,98],"transform":[89,94],"mainly":[90],"contains":[91],"coordinate":[93],"Fourier":[97],"From":[99],"view":[101],"aliasing,":[104],"inter-distance":[106],"sensors":[109],"should":[110],"be":[111,158],"less":[112],"half":[114],"minimum":[117],"wavelength":[118],"signal.":[121],"However,":[122],"bijection":[125],"new":[128,150],"beamforming":[132],"perspective,":[133],"paper":[135],"proposes":[136],"lower":[139],"upper":[141],"bounds":[142],"for":[143],"inter-distance.":[145],"Within":[146],"these":[147],"bounds,":[148],"bijective":[154],"which":[156],"can":[157],"applied":[159],"design":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
