{"id":"https://openalex.org/W2790551406","doi":"https://doi.org/10.1109/cisp-bmei.2017.8302094","title":"LFMCW radar multi-target parameter estimation based on maximum likelihood and keystone transform","display_name":"LFMCW radar multi-target parameter estimation based on maximum likelihood and keystone transform","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2790551406","doi":"https://doi.org/10.1109/cisp-bmei.2017.8302094","mag":"2790551406"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2017.8302094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2017.8302094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5008881208","display_name":"Rui Huang","orcid":"https://orcid.org/0000-0001-8439-4526"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Huang","raw_affiliation_strings":["ATR Lab., National University of Defense Technology NUDT, Changsha, China"],"affiliations":[{"raw_affiliation_string":"ATR Lab., National University of Defense Technology NUDT, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008721449","display_name":"Xiaoyong Du","orcid":"https://orcid.org/0000-0002-5757-9135"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao-Yong Du","raw_affiliation_strings":["ATR Lab., National University of Defense Technology NUDT, Changsha, China"],"affiliations":[{"raw_affiliation_string":"ATR Lab., National University of Defense Technology NUDT, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101593343","display_name":"Weidong Hu","orcid":"https://orcid.org/0009-0004-9129-9702"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei-Dong Hu","raw_affiliation_strings":["ATR Lab., National University of Defense Technology NUDT, Changsha, China"],"affiliations":[{"raw_affiliation_string":"ATR Lab., National University of Defense Technology NUDT, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008881208"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.5444,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80684595,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"33","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9976000189781189,"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.991100013256073,"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/estimator","display_name":"Estimator","score":0.8303322792053223},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.6264011859893799},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5979930758476257},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.5910459160804749},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5795451998710632},{"id":"https://openalex.org/keywords/cram\u00e9r\u2013rao-bound","display_name":"Cram\u00e9r\u2013Rao bound","score":0.5769987106323242},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5208257436752319},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48839157819747925},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.48368579149246216},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.4290663003921509},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41316795349121094},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38693130016326904},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14317432045936584},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12336269021034241}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8303322792053223},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.6264011859893799},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5979930758476257},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.5910459160804749},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5795451998710632},{"id":"https://openalex.org/C4978587","wikidata":"https://www.wikidata.org/wiki/Q1138810","display_name":"Cram\u00e9r\u2013Rao bound","level":3,"score":0.5769987106323242},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5208257436752319},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48839157819747925},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.48368579149246216},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.4290663003921509},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41316795349121094},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38693130016326904},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14317432045936584},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12336269021034241},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2017.8302094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2017.8302094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/W2043004385","https://openalex.org/W2090323666","https://openalex.org/W2101503536","https://openalex.org/W2147016563","https://openalex.org/W2165394398","https://openalex.org/W2196910143","https://openalex.org/W2255565473","https://openalex.org/W2392356450","https://openalex.org/W2558358626","https://openalex.org/W2593687808"],"related_works":["https://openalex.org/W1479746946","https://openalex.org/W2055757274","https://openalex.org/W2511739151","https://openalex.org/W2143803213","https://openalex.org/W2155014562","https://openalex.org/W2134404114","https://openalex.org/W1964936841","https://openalex.org/W2585557503","https://openalex.org/W2026659681","https://openalex.org/W2120595071"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,9,31,44,48,52,59,66,75,87,90,99,110,115,119,127,130,136,147],"migration":[3],"through":[4],"range":[5],"cells(MTRC)":[6],"resulting":[7],"from":[8],"long":[10],"coherent":[11],"processing":[12],"interval":[13],"in":[14],"linear":[15],"frequency":[16],"modulation":[17],"continuous":[18],"wave(LFMCW)":[19],"radar,":[20],"an":[21],"approximate":[22],"maximum":[23,100],"likelihood(AML)":[24],"estimator":[25,93,102],"is":[26,70,121,141],"proposed":[27,91],"to":[28,42,57,109],"deal":[29],"with":[30,62],"parameter":[32],"estimation":[33],"of":[34,47,54,68,89,98,118,126,132,135,146],"multiple":[35],"moving":[36],"targets.":[37],"It":[38],"uses":[39],"Keystone":[40,137],"transform":[41,138],"obtain":[43],"initial":[45],"values":[46],"parameters":[49],"and":[50,103],"applies":[51],"strategy":[53],"step-by-step":[55],"refinement":[56],"maximize":[58],"likelihood":[60],"function":[61],"high":[63],"accuracy.":[64],"Meanwhile,":[65],"process":[67],"CLEAN":[69],"also":[71],"applied":[72],"so":[73],"that":[74,86,97,125,145],"target":[76],"echoes":[77],"were":[78],"processed":[79],"one":[80],"by":[81,153],"one.":[82],"Experimental":[83],"results":[84],"show":[85],"performance":[88,151],"AML":[92,148],"degrades":[94,152],"slightly":[95,142],"than":[96,124,144],"likelihood(ML)":[101],"their":[104],"variances":[105],"are":[106],"all":[107],"close":[108],"Cramer-Rao":[111],"Lower":[112],"Bound(CRLB),":[113],"but":[114],"computational":[116,133],"burden":[117],"former":[120],"much":[122],"lower":[123],"latter.":[128],"Although":[129],"amount":[131],"operations":[134],"based":[139],"algorithm":[140],"less":[143],"estimator,":[149],"its":[150],"2dB":[154],"either.":[155]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}