Two-Dimensional Microwave Tomographic Algorithm for Radar Imaging Through Multilayered Media

Abstract

Abstract-The imaging of targets embedded in a planar layered background media has been an important topic in subsurface and urban sensing. In this paper a fast and efficient tomographic algorithm for the imaging of targets embedded in a multilayered media is presented. The imaging algorithm is based on the first-order Born approximation and exploits the spectral multilayered media Green's function. The exploding reflection model is employed and then the Green's function is expanded in the spectral form to facilitate the easy implementation of the imaging algorithm with fast Fourier transform (FFT). The wave propagation effect due to the presence of the layered subsurface media is automatically taken into account in the imaging formulation through the multilayer media Green's function. The linearization of the inversion scheme and employment of FFT make the imaging algorithm suitable in several applications concerning the diagnostics of large probed domain and allow real-time processing. Representative examples are presented to show the effectiveness and efficiency of the proposed algorithm for radar imaging through multilayered media.

Two- and Three-Dimensional Fast Intrawall Imaging with Microwave Tomographic Algorithm

“…where L a is the adjoint operator of L and maps the scattered field from the data space to the target space [24,25],…”

“…However, the exact calculation of the dyadic Green's function requires the evaluation of the Sommerfeld integral, which is generally complicated and computationally expensive. To simplify and accelerate the imaging speed, the assumption of exploding reflection model is used [24,26],…”

Sparse Electromagnetic Imaging Using Nonlinear Landweber Iterations

“…At Step 4, operator ∂tf * (t) is the adjoint of the operator ∂tf (t), which is the Frechet derivative of the nonlinear function f (t). Operator ∂tf (t) is obtained from (9) as [25]: (12) where matricesF andH are given in (6) and (8), respectively, whileM is expressed as…”

“…More specifically, at the ith iteration, matricesF [see (9)] andM [see (12)] are inverted to compute f (t (i) ) and ∂ t f * |t =t (i) r (i) . These matrix inversions are carried out iteratively using the stabilized bi-conjugate gradient (STABICG) method.…”

“…Numerical methods for solving the inverse scattering problem are called for in various applications in engineering including but not limited to through-wall and tomography imaging [4][5][6], non-destructive testing [7], crack/mine detection [8,9], hydrocarbon reservoir exploration and monitoring [10,11], and radar and remote sensing [12][13][14]. Despite the vast amount of application areas, formulating and implementing efficient and accurate inverse solvers is still a challenging task.…”