Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3967
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dc.contributor.authorMishra, Abhijit-
dc.contributor.authorSahoo, Upendra Kumar-
dc.contributor.authorMaiti, Subrata-
dc.date.accessioned2023-03-09T07:18:06Z-
dc.date.available2023-03-09T07:18:06Z-
dc.date.issued2023-02-
dc.identifier.citation29th National Conference on Communications (NCC), IIT Guwahati, 23-26 February 2023en_US
dc.identifier.urihttp://hdl.handle.net/2080/3967-
dc.descriptionCopyright belongs to proceeding publisheren_US
dc.description.abstractThe device-free localization (DFL) technique for target localization and tracking in a wireless sensor network is important in modern research. Radio tomographic imaging (RTI) is a DFL method that is widely used in today’s imagebased localization systems. In the RTI system, spatial loss fields (SLFs) represent the maps that indicate the degree of radio wave attenuation for each spatial location in the WSN due to obstacles. In the real-world RTI model, the data is always perturbed by uncertainty. Therefore, uncertainty in sensor node location leads to uncertainty in the input data of the RTI regression model. To address the sensor location uncertainty problem, this paper proposes a novel stochastic robust approximation (SRA) method for RTI (SRA-RTI). Simulation-based performance analysis shows that the proposed technique is robust against the uncertainty in the sensor node location.en_US
dc.subjectRadio tomographic imagingen_US
dc.subjectreceived signal strengthen_US
dc.subjectspatial loss fielden_US
dc.subjectstochastic robust approximationen_US
dc.titleRadio Tomographic Imaging with Input Sensor Location Uncertaintyen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

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