Detection, localization and reconstruction of images (3D / 2D) of below ground targets based upon RF tomography is a process using multistatic antenna (Transmitters and Receivers) configuration of randomly distributed over the measurement domain. In this paper, an effective method for RF tomography image enhancement is presented. The interference between strong scatterer sidelobes and weak scatterers in the measurement domain, leading to a decrease in the image quality and also can mask the returns from nearby weak targets in Rf Tomography. We propose a faster, more flexible and accurate method to deal with ill-conditioned operators in RF tomography, we decrease the effects of strong sidelobes on targets which increases the potential to reconstruct quality images of buried weak targets using an Iterative Reconstruction Algorithms (IRT), such as Multiplicative Algebraic Reconstruction Techniques (MART). The MART algorithm is an iterative algebraic approach that inverts the linear operator with less computational expense when the operator is ill-conditioned. Suppression, or the clean algorithm is an effective approach to remove the effect of strong sidelobes from dominant scatterers on nearby weak targets in the measurement domain. This algorithm functions by modeling the strong scatterers as extra transmitters in the measurement domain. The sidelobes of these dipoles are subtracted from the collected field to sharpen the quality of the weak targets image. Simulation data using the computational electromagnetic software FEKO are used to validate a inversion scheme, based on an Iterative Reconstruction Algorithms (IRT), such as Multiplicative Algebraic Reconstruction Techniques (MART), and the proposed suppression algorithm.
Suppression of Strong Sidelobes Masking Weak Targets Using Multiplicative Algebraic Reconstruction Techniques (MART)
2018-07-01
944432 byte
Conference paper
Electronic Resource
English
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