NDLI: Optimal linear filtering for weak target detection based on dyadic contrast function analysis in RFT

Content Provider	IET Digital Library
Author	Akroush, Muftah E. Wicks, Michael C.
Abstract	In this study, a forward model for radio frequency tomography (RFT) is improved to remove the effect of strong sidelobes from dominant scatterers in the region of interest. This approach uses a ‘suppression algorithm (SA)’ to remove the effect of strong sidelobes on weak targets. SA is used to remove the effect of these strong sidelobes using the information from the dyadic contrast function (DCF). DCF is analysed in order to remove the effects of strong sidelobes generated by dominant cells in the measurement domain. The eigenvalues and eigenvectors for dominant cells are obtained to remodel the strong cells as a secondary source in the measurement scene. Furthermore, to simplify the inversion problem in the new forward model, iterative reconstruction algorithms is considered. Subsurface multiplicative algebraic reconstruction technique as additive technique is proposed to solve the new forward model RFT with less computing power and memory. The presented algorithm has been verified using simulated RFT data, generated by the computational electromagnetic software FEKO, for regular and irregular targets scenarios. The proposed research shows that using information from the DCF it is possible to obtain high quality imagery of buried weak targets in RFT.
Starting Page	773
Ending Page	781
Page Count	9
ISSN	17518784
Volume Number	14
e-ISSN	17518792
Issue Number	Issue 5, May (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/14/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2019.0346
Journal	IET Radar, Sonar & Navigation
Publisher Date	2020-02-03
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Buried Weak Targets Computational Electromagnetics Computer Vision And Image Processing Technique Dominant Cell Dominant Scatterers Dyadic Contrast Function Analysis Eigen Values And Eigen Function Electromagnetic Wave Scattering Filtering Method in Signal Processing Filtering Theory Forward Model RFT Image Reconstruction Interpolation And Function Approximation Inverse Problem Iterative Method Numerical Analysis Object Detection Optical, Image And Video Signal Processing Radio Frequency Tomography Simulated RFT Data Strong Cell Strong Sidelobes Tomography Weak Target Detection
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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