{"id":"https://openalex.org/W7161129667","doi":"https://doi.org/10.48550/arxiv.2605.12569","title":"Active Sensing with Meta-Reinforcement Learning for Emitter Localization from RF Observations","display_name":"Active Sensing with Meta-Reinforcement Learning for Emitter Localization from RF Observations","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W7161129667","doi":"https://doi.org/10.48550/arxiv.2605.12569"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.12569","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12569","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.12569","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136163583","display_name":"M. Shamail J. Khan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, M. Shamail J.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136135911","display_name":"Nisha L. Raichur","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raichur, Nisha L.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073940195","display_name":"Lucas Heublein","orcid":"https://orcid.org/0000-0001-6670-3698"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heublein, Lucas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120152382","display_name":"Christian Wielenberg","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wielenberg, Christian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015218576","display_name":"Alexander Mattick","orcid":"https://orcid.org/0000-0001-7805-199X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mattick, Alexander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015986195","display_name":"Tobias Feigl","orcid":"https://orcid.org/0000-0002-3040-3543"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feigl, Tobias","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023277657","display_name":"Christopher Mutschler","orcid":"https://orcid.org/0000-0001-8108-0230"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mutschler, Christopher","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136151192","display_name":"Felix Ott","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ott, Felix","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.7937999963760376,"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"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.7937999963760376,"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"}},{"id":"https://openalex.org/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.030700000002980232,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.024700000882148743,"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/gnss-applications","display_name":"GNSS applications","score":0.7046999931335449},{"id":"https://openalex.org/keywords/multipath-propagation","display_name":"Multipath propagation","score":0.6520000100135803},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.6470999717712402},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5181999802589417},{"id":"https://openalex.org/keywords/common-emitter","display_name":"Common emitter","score":0.49790000915527344},{"id":"https://openalex.org/keywords/multipath-interference","display_name":"Multipath interference","score":0.4043999910354614},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.39879998564720154},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.3880999982357025},{"id":"https://openalex.org/keywords/electromagnetic-interference","display_name":"Electromagnetic interference","score":0.3849000036716461}],"concepts":[{"id":"https://openalex.org/C14279187","wikidata":"https://www.wikidata.org/wiki/Q5514012","display_name":"GNSS applications","level":3,"score":0.7046999931335449},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6887999773025513},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.6520000100135803},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.6470999717712402},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5181999802589417},{"id":"https://openalex.org/C46918542","wikidata":"https://www.wikidata.org/wiki/Q1648344","display_name":"Common emitter","level":2,"score":0.49790000915527344},{"id":"https://openalex.org/C174749922","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath interference","level":4,"score":0.4043999910354614},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.39879998564720154},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3880999982357025},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3880000114440918},{"id":"https://openalex.org/C184892835","wikidata":"https://www.wikidata.org/wiki/Q1474513","display_name":"Electromagnetic interference","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C2778027091","wikidata":"https://www.wikidata.org/wiki/Q25346003","display_name":"Satellite system","level":4,"score":0.38190001249313354},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.358599990606308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3434999883174896},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C202311505","wikidata":"https://www.wikidata.org/wiki/Q1474701","display_name":"Radio propagation","level":2,"score":0.32589998841285706},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.3215999901294708},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C36301306","wikidata":"https://www.wikidata.org/wiki/Q179435","display_name":"Satellite navigation","level":3,"score":0.3027999997138977},{"id":"https://openalex.org/C2776015439","wikidata":"https://www.wikidata.org/wiki/Q25313558","display_name":"Multipath mitigation","level":4,"score":0.3018999993801117},{"id":"https://openalex.org/C74064498","wikidata":"https://www.wikidata.org/wiki/Q3396184","display_name":"Radio frequency","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.26829999685287476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.12569","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12569","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.12569","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12569","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.41443198919296265,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Global":[0],"navigation":[1],"satellite":[2],"system":[3],"(GNSS)":[4],"interference":[5,31,181,195],"poses":[6],"a":[7,40,68,78,141,167,190],"serious":[8],"threat":[9],"to":[10,53],"reliable":[11],"positioning,":[12],"especially":[13],"in":[14,45,197],"indoor":[15],"and":[16,38,92,109,117,124,129,155],"multipath-rich":[17],"environments":[18],"where":[19],"source":[20,60],"localization":[21,32,73,168,196],"is":[22,75,138],"highly":[23],"challenging.":[24],"In":[25],"this":[26],"paper,":[27],"we":[28],"formulate":[29],"GNSS":[30,180],"as":[33,77,189],"an":[34,47,58],"active":[35],"sensing":[36,105],"problem":[37],"propose":[39],"reinforcement":[41],"learning":[42],"(RL)":[43],"framework":[44,101],"which":[46,150],"agent":[48],"sequentially":[49],"explores":[50],"the":[51,55,99,146,163,174,184],"environment":[52,157],"infer":[54],"position":[56],"of":[57,171,176],"emitter":[59],"from":[61],"radio":[62],"frequency":[63],"(RF)":[64],"observations":[65],"acquired":[66],"with":[67,106,145],"2x2":[69],"patch":[70],"antenna.":[71],"The":[72,136],"task":[74],"modeled":[76],"partially":[79],"observable":[80],"decision":[81],"process,":[82],"since":[83],"single-snapshot":[84],"measurements":[85],"are":[86],"often":[87],"ambiguous":[88],"under":[89,133],"multipath":[90],"propagation":[91,153,199],"changing":[93],"channel":[94],"conditions.":[95],"To":[96],"address":[97],"this,":[98],"proposed":[100,164],"combines":[102],"high-dimensional":[103],"RF":[104],"deep":[107],"RL":[108,177],"recurrent":[110],"policy":[111],"learning.":[112],"We":[113],"investigate":[114],"both":[115],"value-based":[116],"policy-based":[118],"approaches,":[119],"namely":[120],"Deep":[121],"Q-Networks":[122],"(DQN)":[123],"Proximal":[125],"Policy":[126],"Optimization":[127],"(PPO),":[128],"study":[130],"their":[131],"behavior":[132],"domain":[134],"shift.":[135],"approach":[137],"evaluated":[139],"on":[140],"simulated":[142],"dataset":[143],"generated":[144],"Sionna":[147],"ray-tracing":[148],"module,":[149],"provides":[151],"realistic":[152],"effects":[154],"diverse":[156],"configurations.":[158],"Experimental":[159],"results":[160,185],"show":[161],"that":[162],"method":[165],"achieves":[166],"success":[169],"rate":[170],"80.1%,":[172],"demonstrating":[173],"potential":[175],"for":[178,193],"adaptive":[179],"localization.":[182],"Overall,":[183],"highlight":[186],"simulation-assisted":[187],"training":[188],"promising":[191],"direction":[192],"robust":[194],"challenging":[198],"environments.":[200]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-15T00:00:00"}