{"id":"https://openalex.org/W4414538692","doi":"https://doi.org/10.1109/icc52391.2025.11160916","title":"Self-Supervised Deep State Space Model for Enhanced Indoor Tracking","display_name":"Self-Supervised Deep State Space Model for Enhanced Indoor Tracking","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414538692","doi":"https://doi.org/10.1109/icc52391.2025.11160916"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11160916","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11160916","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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/A5114246682","display_name":"Geng Wang","orcid":"https://orcid.org/0009-0004-2832-4207"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Geng Wang","raw_affiliation_strings":["School of Electrical and Computer Engineering, The University of Sydney,Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, The University of Sydney,Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021052588","display_name":"Peng Cheng","orcid":"https://orcid.org/0000-0003-1091-7894"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Peng Cheng","raw_affiliation_strings":["La Trobe University,Department of Computer Science and Information Technology,Australia"],"affiliations":[{"raw_affiliation_string":"La Trobe University,Department of Computer Science and Information Technology,Australia","institution_ids":["https://openalex.org/I196829312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100673375","display_name":"Shenghong Li","orcid":"https://orcid.org/0000-0002-5516-9394"},"institutions":[{"id":"https://openalex.org/I1292875679","display_name":"Commonwealth Scientific and Industrial Research Organisation","ror":"https://ror.org/03qn8fb07","country_code":"AU","type":"funder","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shenghong Li","raw_affiliation_strings":["Data 61, CSIRO,Australia"],"affiliations":[{"raw_affiliation_string":"Data 61, CSIRO,Australia","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I1292875679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060894111","display_name":"Youjia Chen","orcid":"https://orcid.org/0000-0002-6430-2003"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youjia Chen","raw_affiliation_strings":["College of Physics and Information Engineering, Fuzhou University,China"],"affiliations":[{"raw_affiliation_string":"College of Physics and Information Engineering, Fuzhou University,China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043371405","display_name":"Branka Vucetic","orcid":"https://orcid.org/0000-0002-2700-2001"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Branka Vucetic","raw_affiliation_strings":["School of Electrical and Computer Engineering, The University of Sydney,Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, The University of Sydney,Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100448724","display_name":"Yonghui Li","orcid":"https://orcid.org/0000-0001-7702-1123"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yonghui Li","raw_affiliation_strings":["School of Electrical and Computer Engineering, The University of Sydney,Australia"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, The University of Sydney,Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5114246682"],"corresponding_institution_ids":["https://openalex.org/I129604602"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27696527,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"692","last_page":"697"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9261999726295471,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9261999726295471,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/tracking","display_name":"Tracking (education)","score":0.7932000160217285},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6025000214576721},{"id":"https://openalex.org/keywords/tracking-system","display_name":"Tracking system","score":0.5178999900817871},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4781999886035919},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.45649999380111694},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.4449999928474426},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.42809998989105225},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4189999997615814}],"concepts":[{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.7932000160217285},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6269000172615051},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6025000214576721},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5619999766349792},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.5178999900817871},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49309998750686646},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4781999886035919},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.45649999380111694},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.4449999928474426},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.42809998989105225},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4189999997615814},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.41179999709129333},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.39399999380111694},{"id":"https://openalex.org/C187107819","wikidata":"https://www.wikidata.org/wiki/Q835696","display_name":"NASA Deep Space Network","level":3,"score":0.3463999927043915},{"id":"https://openalex.org/C52918065","wikidata":"https://www.wikidata.org/wiki/Q230945","display_name":"State-space representation","level":2,"score":0.33059999346733093},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.32249999046325684},{"id":"https://openalex.org/C194232998","wikidata":"https://www.wikidata.org/wiki/Q1606712","display_name":"Transition (genetics)","level":3,"score":0.3050999939441681},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C61776360","wikidata":"https://www.wikidata.org/wiki/Q5250441","display_name":"Deep space exploration","level":4,"score":0.2824000120162964},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.2784999907016754},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc52391.2025.11160916","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11160916","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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":18,"referenced_works":["https://openalex.org/W1538441114","https://openalex.org/W2143737806","https://openalex.org/W2885195348","https://openalex.org/W2972355358","https://openalex.org/W3033032209","https://openalex.org/W3155991567","https://openalex.org/W3201337335","https://openalex.org/W3217536461","https://openalex.org/W4210560670","https://openalex.org/W4249545676","https://openalex.org/W4312556654","https://openalex.org/W4313156720","https://openalex.org/W4361029849","https://openalex.org/W4386158948","https://openalex.org/W4387717417","https://openalex.org/W4389372489","https://openalex.org/W4402833543","https://openalex.org/W4403331794"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"indoor":[1,18,58],"tracking":[2,26,59,136],"is":[3],"a":[4,49],"critical":[5],"component":[6],"of":[7,72,85,97,129],"modern":[8],"location-based":[9],"services,":[10],"fundamentally":[11],"transforming":[12],"the":[13,82,89,94,115],"way":[14],"we":[15,47],"interact":[16],"with":[17],"environments.":[19],"Traditional":[20],"state":[21,52],"space":[22,53],"model":[23,54,106],"(SSM)":[24],"based":[25],"often":[27],"struggles":[28],"in":[29,70],"complex":[30,95],"environments":[31],"due":[32],"to":[33,91,110,139],"its":[34,134],"reliance":[35],"on":[36],"fixed":[37,73],"and":[38,41,75,101],"oversimplified":[39],"transition":[40,74],"observation":[42,76],"functions.":[43,77],"In":[44],"this":[45],"paper,":[46],"propose":[48],"novel":[50],"deep":[51],"(DSSM)":[55],"approach":[56],"for":[57,117],"that":[60],"overcomes":[61],"these":[62],"limitations":[63],"by":[64],"leveraging":[65],"trainable":[66],"neural":[67],"networks":[68],"(NNs)":[69],"place":[71],"The":[78,104],"proposed":[79,105],"DSSM":[80],"retains":[81],"structured":[83],"representation":[84],"SSMs":[86],"while":[87],"improving":[88],"ability":[90],"effectively":[92],"capture":[93],"dynamics":[96],"both":[98],"target":[99],"movements":[100],"measurement":[102],"errors.":[103],"incorporates":[107],"physics":[108],"constraints":[109],"enable":[111],"self-supervised":[112],"learning,":[113],"eliminating":[114],"need":[116],"labeled":[118],"data":[119],"during":[120],"training.":[121],"We":[122],"evaluate":[123],"our":[124],"framework":[125],"using":[126],"real-world":[127],"time":[128],"flight":[130],"(ToF)":[131],"measurements,":[132],"demonstrating":[133],"superior":[135],"accuracy":[137],"compared":[138],"conventional":[140],"methods.":[141]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}