Matches in SemOpenAlex for { <https://semopenalex.org/work/W2891671729> ?p ?o ?g. }
- W2891671729 endingPage "3110" @default.
- W2891671729 startingPage "3110" @default.
- W2891671729 abstract "Device-free localization (DFL) that aims to localize targets without carrying any electronic devices is addressed as an emerging and promising research topic. DFL techniques estimate the locations of transceiver-free targets by analyzing their shadowing effects on the radio signals that travel through the area of interest. Recently, compressive sensing (CS) theory has been applied in DFL to reduce the number of measurements by exploiting the inherent spatial sparsity of target locations. In this paper, we propose a novel CS-based multi-target DFL method to leverage the frequency diversity of fine-grained subcarrier information. Specifically, we build the dictionaries of multiple channels based on the saddle surface model and formulate the multi-target DFL as a joint sparse recovery problem. To estimate the location vector, an iterative location vector estimation algorithm is developed under the multitask Bayesian compressive sensing (MBCS) framework. Compared with the state-of-the-art CS-based multi-target DFL approaches, simulation results validate the superiority of the proposed algorithm." @default.
- W2891671729 created "2018-09-27" @default.
- W2891671729 creator A5007631678 @default.
- W2891671729 creator A5009292756 @default.
- W2891671729 creator A5031810848 @default.
- W2891671729 date "2018-09-14" @default.
- W2891671729 modified "2023-10-09" @default.
- W2891671729 title "Exploiting Fine-Grained Subcarrier Information for Device-Free Localization in Wireless Sensor Networks" @default.
- W2891671729 cites W1033446481 @default.
- W2891671729 cites W1941817920 @default.
- W2891671729 cites W1986931325 @default.
- W2891671729 cites W1988348999 @default.
- W2891671729 cites W2000721204 @default.
- W2891671729 cites W2006036128 @default.
- W2891671729 cites W2014758824 @default.
- W2891671729 cites W2031721930 @default.
- W2891671729 cites W2071284784 @default.
- W2891671729 cites W2093347109 @default.
- W2891671729 cites W2106806426 @default.
- W2891671729 cites W2107300377 @default.
- W2891671729 cites W2119667497 @default.
- W2891671729 cites W2122623239 @default.
- W2891671729 cites W2126300356 @default.
- W2891671729 cites W2127271355 @default.
- W2891671729 cites W2127870457 @default.
- W2891671729 cites W2129131372 @default.
- W2891671729 cites W2143228105 @default.
- W2891671729 cites W2148154358 @default.
- W2891671729 cites W2155892418 @default.
- W2891671729 cites W2164692160 @default.
- W2891671729 cites W2294724112 @default.
- W2891671729 cites W2309512289 @default.
- W2891671729 cites W2338095309 @default.
- W2891671729 cites W2391401965 @default.
- W2891671729 cites W2403386687 @default.
- W2891671729 cites W2511885285 @default.
- W2891671729 cites W2517587710 @default.
- W2891671729 cites W2524700105 @default.
- W2891671729 cites W2526606216 @default.
- W2891671729 cites W2538535315 @default.
- W2891671729 cites W2560262977 @default.
- W2891671729 cites W2578622953 @default.
- W2891671729 cites W2586549589 @default.
- W2891671729 cites W2591820339 @default.
- W2891671729 cites W2607236313 @default.
- W2891671729 cites W2735507411 @default.
- W2891671729 cites W2736051620 @default.
- W2891671729 cites W2743415265 @default.
- W2891671729 cites W2764026391 @default.
- W2891671729 cites W2789857179 @default.
- W2891671729 cites W3136666733 @default.
- W2891671729 cites W4250955649 @default.
- W2891671729 doi "https://doi.org/10.3390/s18093110" @default.
- W2891671729 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6164765" @default.
- W2891671729 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30223537" @default.
- W2891671729 hasPublicationYear "2018" @default.
- W2891671729 type Work @default.
- W2891671729 sameAs 2891671729 @default.
- W2891671729 citedByCount "7" @default.
- W2891671729 countsByYear W28916717292019 @default.
- W2891671729 countsByYear W28916717292020 @default.
- W2891671729 countsByYear W28916717292021 @default.
- W2891671729 countsByYear W28916717292022 @default.
- W2891671729 crossrefType "journal-article" @default.
- W2891671729 hasAuthorship W2891671729A5007631678 @default.
- W2891671729 hasAuthorship W2891671729A5009292756 @default.
- W2891671729 hasAuthorship W2891671729A5031810848 @default.
- W2891671729 hasBestOaLocation W28916717291 @default.
- W2891671729 hasConcept C113775141 @default.
- W2891671729 hasConcept C124851039 @default.
- W2891671729 hasConcept C127162648 @default.
- W2891671729 hasConcept C127413603 @default.
- W2891671729 hasConcept C152139883 @default.
- W2891671729 hasConcept C153083717 @default.
- W2891671729 hasConcept C154945302 @default.
- W2891671729 hasConcept C198329298 @default.
- W2891671729 hasConcept C24326235 @default.
- W2891671729 hasConcept C31258907 @default.
- W2891671729 hasConcept C40409654 @default.
- W2891671729 hasConcept C41008148 @default.
- W2891671729 hasConcept C555944384 @default.
- W2891671729 hasConcept C76155785 @default.
- W2891671729 hasConcept C7720470 @default.
- W2891671729 hasConcept C79403827 @default.
- W2891671729 hasConceptScore W2891671729C113775141 @default.
- W2891671729 hasConceptScore W2891671729C124851039 @default.
- W2891671729 hasConceptScore W2891671729C127162648 @default.
- W2891671729 hasConceptScore W2891671729C127413603 @default.
- W2891671729 hasConceptScore W2891671729C152139883 @default.
- W2891671729 hasConceptScore W2891671729C153083717 @default.
- W2891671729 hasConceptScore W2891671729C154945302 @default.
- W2891671729 hasConceptScore W2891671729C198329298 @default.
- W2891671729 hasConceptScore W2891671729C24326235 @default.
- W2891671729 hasConceptScore W2891671729C31258907 @default.
- W2891671729 hasConceptScore W2891671729C40409654 @default.
- W2891671729 hasConceptScore W2891671729C41008148 @default.
- W2891671729 hasConceptScore W2891671729C555944384 @default.
- W2891671729 hasConceptScore W2891671729C76155785 @default.