Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3563
Title: Distributed Incremental Strategy for Radio Tomographic Imaging
Authors: Abhijit, Mishra
Upendra Ku., Sahu
Subrata, Maiti
Keywords: Radio tomography
tomographic imaging
Spatialloss field
regularization methods
Distributed Incremental RTI
Issue Date: Dec-2020
Citation: INDICON-2020 organized virtually by NSUT, NEW DELHI on 11-13 December 2020
Abstract: Radio Tomographic Imaging (RTI) finds extensiveapplication in modern day problem. The RTI achieved this usingreceived signal strength (RSS) power and transmitted power bysensor nodes. RTI being an ill-posed inverse problem, requiresregularization for proper estimation of spatial loss field(SLF)and able to detect the object. Centralized solution of RTIsystem requires large communication overheads. This motivatesto develop distributed algorithm for RTI. Two novel distributedalgorithms using incremental approach are developed in thispaper. The first approach is the direct extension of the centralizedapproach to distributed incremental approach. Second algorithmrequires less communication overheads compared to the firstone by incorporating data censoring technique. The performancemetrics show that the performance of distributed IncrementalRTI is comparable to the centralized RTI system. Again theimpact of censoring is studied by increasing the censoring ratio ,which results in a trade-off between detection performance andcomputational complexity
Description: Copyright of this paper is with proceedings publisher
URI: http://hdl.handle.net/2080/3563
Appears in Collections:Conference Papers

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