{"id":"https://openalex.org/W4414432815","doi":"https://doi.org/10.1109/case58245.2025.11163933","title":"Cross-Scale Clustering and Neighborhood-Weighted Motion Pattern Extraction for Radar Trajectory Analysis<sup>*</sup>","display_name":"Cross-Scale Clustering and Neighborhood-Weighted Motion Pattern Extraction for Radar Trajectory Analysis<sup>*</sup>","publication_year":2025,"publication_date":"2025-08-17","ids":{"openalex":"https://openalex.org/W4414432815","doi":"https://doi.org/10.1109/case58245.2025.11163933"},"language":"en","primary_location":{"id":"doi:10.1109/case58245.2025.11163933","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case58245.2025.11163933","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Automation Science and Engineering (CASE)","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/A5100332232","display_name":"Ziqian Wang","orcid":"https://orcid.org/0009-0006-9496-2244"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziqian Wang","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China,100049"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China,100049","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100453754","display_name":"Li\u2010Fang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162172","display_name":"Chinese People\u2019s Liberation Army 263 hospital","ror":"https://ror.org/05b51ak88","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210162172"]},{"id":"https://openalex.org/I4210160531","display_name":"Chinese People's Liberation Army","ror":"https://ror.org/05tf9r976","country_code":"CN","type":"funder","lineage":["https://openalex.org/I4210160531"]},{"id":"https://openalex.org/I4210145476","display_name":"Chinese People 's Liberation Army No. 85 Hospital","ror":"https://ror.org/04bda0170","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210145476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lifang Zhang","raw_affiliation_strings":["The Chinese People&#x2019;s Liberation Army Unit,93209"],"affiliations":[{"raw_affiliation_string":"The Chinese People&#x2019;s Liberation Army Unit,93209","institution_ids":["https://openalex.org/I4210160531","https://openalex.org/I4210162172","https://openalex.org/I4210145476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112724309","display_name":"Yuxin Guo","orcid":"https://orcid.org/0009-0008-5036-2575"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxin Guo","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China,100049"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China,100049","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050531685","display_name":"Hu Su","orcid":"https://orcid.org/0000-0002-0551-3193"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hu Su","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS),Beijing,China,100190"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS),Beijing,China,100190","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108286207","display_name":"Wei Zou","orcid":"https://orcid.org/0000-0003-4215-5361"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zou","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS),Beijing,China,100190"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS),Beijing,China,100190","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I4210100255"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022867743","display_name":"Hongxuan Ma","orcid":"https://orcid.org/0000-0001-6422-1441"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxuan Ma","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS),Beijing,China,100190"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS),Beijing,China,100190","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I4210100255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100332232"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26407909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"947","last_page":"953"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9589999914169312,"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"}},"topics":[{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9589999914169312,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9445000290870667,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9289000034332275,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.8080999851226807},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7750999927520752},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5537999868392944},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5210000276565552},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.462799996137619},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4041000008583069},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.3711000084877014}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8080999851226807},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7750999927520752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6481000185012817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6308000087738037},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5537999868392944},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5210000276565552},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49970000982284546},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.462799996137619},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.3711000084877014},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.3352999985218048},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31949999928474426},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.25609999895095825},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/case58245.2025.11163933","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case58245.2025.11163933","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1966554111","https://openalex.org/W1981398125","https://openalex.org/W1981934656","https://openalex.org/W1987971958","https://openalex.org/W2044023374","https://openalex.org/W2072957930","https://openalex.org/W2076943964","https://openalex.org/W2139515907","https://openalex.org/W2151263703","https://openalex.org/W2160642098","https://openalex.org/W2322990480","https://openalex.org/W2336558992","https://openalex.org/W2969079355","https://openalex.org/W2995324203","https://openalex.org/W4213418104","https://openalex.org/W4285781363","https://openalex.org/W4312222690"],"related_works":[],"abstract_inverted_index":{"Clustering":[0],"and":[1,30,41,50,77,120,130,184,190],"motion":[2,51,80,108,122,194],"pattern":[3,52,109],"extraction":[4,110],"of":[5,14,21,27,33,70,151,161,167,181],"radar":[6,67,145],"trajectories":[7,40,72,97,126,141],"with":[8,98,127],"the":[9,19,25,31,84,107,148,165,168,179],"same":[10],"flight":[11,22,28],"route":[12],"are":[13],"great":[15],"significance":[16],"for":[17,47,66],"analyzing":[18],"intent":[20,29],"targets.":[23],"However,":[24],"subjectivity":[26],"maneuverability":[32],"targets":[34],"result":[35],"in":[36,83,106],"large":[37],"differences":[38,187],"between":[39],"increased":[42],"trajectory":[43,48,63],"complexity,":[44],"presenting":[45],"challenges":[46],"clustering":[49,71,85,90,189],"extraction.":[53],"To":[54],"address":[55],"these":[56],"issues,":[57],"this":[58,155],"paper":[59],"proposes":[60],"a":[61,87,112,136,159],"novel":[62],"analysis":[64],"algorithm":[65,114],"trajectories,":[68],"capable":[69],"across":[73],"different":[74],"spatial":[75,103,185],"scales":[76],"extracting":[78],"their":[79],"patterns.":[81],"Specifically,":[82],"phase,":[86,111],"cross-scale":[88],"density":[89],"method":[91],"is":[92,115],"proposed":[93,169],"to":[94,117,163],"efficiently":[95],"cluster":[96],"similar":[99],"shapes":[100],"but":[101],"varying":[102],"scales.":[104],"Subsequently,":[105],"neighborhood-weighted":[113],"designed":[116],"extract":[118],"concise":[119],"ordered":[121],"patterns":[123,195],"from":[124,143,196],"complex":[125,197],"multiple":[128],"loops":[129],"repetitive":[131],"movements.":[132],"Finally,":[133],"we":[134,157],"constructed":[135],"large-scale":[137],"dataset":[138],"containing":[139],"2,754":[140],"collected":[142],"real":[144],"data":[146],"throughout":[147],"entire":[149],"year":[150],"2017.":[152],"Based":[153],"on":[154,188],"dataset,":[156],"conducted":[158],"series":[160],"experiments":[162],"verify":[164],"effectiveness":[166],"algorithm.":[170],"Experimental":[171],"results":[172],"show":[173],"that":[174],"our":[175],"approach":[176],"effectively":[177],"overcomes":[178],"impact":[180],"geographical":[182],"location":[183],"scale":[186],"successfully":[191],"extracts":[192],"typical":[193],"trajectories.":[198]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}