摘要 :
We propose a new approach to solve the problem of optimal power synthesis of array antennas, so that maximum possible bandwidth can be granted to fixed sidelobe-level performances. The proposed approach can be applied to any kind ...
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We propose a new approach to solve the problem of optimal power synthesis of array antennas, so that maximum possible bandwidth can be granted to fixed sidelobe-level performances. The proposed approach can be applied to any kind of fixed-geometry array that radiates pencil beams and to linear equispaced arrays that generate shaped patterns. The designing problem is cast as a sequence of Convex Programming optimizations. Numerous numerical experiments, including full-wave synthesis of realistic antennas, were carried out and their results discussed here to assess the array antennas' capability of achieving ultra-wideband performances.
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A new approach providing new theoretical results to the optimal far-field focusing of uniformly spaced arrays, subject to a completely arbitrary mask for sidelobe bounds, is presented and discussed. In both cases of linear or plan...
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A new approach providing new theoretical results to the optimal far-field focusing of uniformly spaced arrays, subject to a completely arbitrary mask for sidelobe bounds, is presented and discussed. In both cases of linear or planar arrays (with rectangular boundaries), it is first shown that the problem can be formulated, without any loss to performances on the maximum, as a linear programming one, guaranteeing a globally optimal solution. Second, a sufficient uniqueness criterion for the solution of the overall problem is also developed, which shows how the solution may not be unique (as is actually the case) when planar arrays are considered. In addition, further globally effective optimization procedures are proposed for the latter case in order to optimize directivity, smoothness of excitations, or other performance parameters in the set of equivalent solutions. Last, an extension to planar arrays with a nonrectangular boundary is also given. A thorough numerical analysis confirms the effectiveness of the approach proposed and of the solution codes developed.
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摘要 :
A new approach providing new theoretical results to the optimal far-field focusing of uniformly spaced arrays, subject to a completely arbitrary mask for sidelobe bounds, is presented and discussed. In both cases of linear or plan...
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A new approach providing new theoretical results to the optimal far-field focusing of uniformly spaced arrays, subject to a completely arbitrary mask for sidelobe bounds, is presented and discussed. In both cases of linear or planar arrays (with rectangular boundaries), it is first shown that the problem can be formulated, without any loss to performances on the maximum, as a linear programming one, guaranteeing a globally optimal solution. Second, a sufficient uniqueness criterion for the solution of the overall problem is also developed, which shows how the solution may not be unique (as is actually the case) when planar arrays are considered. In addition, further globally effective optimization procedures are proposed for the latter case in order to optimize directivity, smoothness of excitations, or other performance parameters in the set of equivalent solutions. Last, an extension to planar arrays with a nonrectangular boundary is also given. A thorough numerical analysis confirms the effectiveness of the approach proposed and of the solution codes developed.
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A nonlinear estimation approach to solving the inverse scattering problem, and reconstructing the space-varying complex permittivity of unknown objects is considered. The bilinear operator equations governing the scattering are ap...
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A nonlinear estimation approach to solving the inverse scattering problem, and reconstructing the space-varying complex permittivity of unknown objects is considered. The bilinear operator equations governing the scattering are approximated into finite dimensional spaces on the basis of the finite degrees of freedom of data, and on the simple concept that one cannot expect to reconstruct an arbitrary function from a finite number of independent equations. As a consequence, a discrete model, well suited to numerical inversion, is developed. The particular bilinear nature of the equations, and a suitable choice of contrast and field unknowns allows the functional adopted in the estimation to be minimized in an accurate and numerically efficient manner. Numerical experiments show how the method is capable, when a proper number of searched unknowns is adopted, to manage the possible convergence to local minima (which is a typical question in nonlinear inverse problems), and validate the effectiveness of the proposed approach.
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A hybrid effective approach is proposed to focus the intensity of a vector field generated by an arbitrary fixed-geometry array antenna into a target point and keep it bounded elsewhere. To overcome the complexity of the underlyin...
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A hybrid effective approach is proposed to focus the intensity of a vector field generated by an arbitrary fixed-geometry array antenna into a target point and keep it bounded elsewhere. To overcome the complexity of the underlying non-convex problem involving a possibly large number of unknowns, we show how the space of possible polarizations can be regarded as a 5-sphere and introduce a nested procedure which jointly relies on an (external) global optimization of the field polarization on the target point plus an (internal) convex optimization of the array excitations. The approach can deal with both the cases of near-field (NF) and far-field (FF) focusing as well as with complex inhomogeneous 3-D media. The high-performance results achieved through full-wave simulations of realistic scenarios confirm the actual feasibility of tackling the problem as a low-dimensional global optimization, so that the best possible focusing can be hopefully realized.
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We propose a new deterministic approach to the synthesis of linear arrays having the least possible number of elements while radiating shaped beams lying in completely arbitrary power masks. The approach takes joint advantage from...
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We propose a new deterministic approach to the synthesis of linear arrays having the least possible number of elements while radiating shaped beams lying in completely arbitrary power masks. The approach takes joint advantage from compressive sensing (CS), from the multiplicity of power patterns lying in a given mask, and from the multiplicity of field solutions corresponding to each of these power patterns. Care is taken in order to exploit the available degrees of freedom in an effective fashion, and in optimizing parameters that affect the CS performance. An extensive numerical comparison against state-of-the-art procedures proves the effectiveness of the approach.
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In this paper, after a brief review on the working principles of synthetic aperture radiometers exploiting interferometry and mechanical rotation of the antenna, analytical expressions are provided which allow to easily compute th...
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In this paper, after a brief review on the working principles of synthetic aperture radiometers exploiting interferometry and mechanical rotation of the antenna, analytical expressions are provided which allow to easily compute the receiving performance of the interferometer starting from given locations of its sensors. Then, an innovative and general approach is developed and discussed for the optimal synthesis of the locations of the array sensors in order to fulfill requirements of crucial interest. Moreover, an innovative approach is also developed for the synthesis of the optimal weighting of the different collected signals. Finally, the performances of the developed synthesis approaches are discussed with reference to the GEO Atmospheric Sounder (GAS) array instrument.
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A new approach to the optimal focusing of array fields subject to arbitrary upper bounds is presented. The approach formulates the problem as the minimization of a linear function in a convex set. Unlike other approaches, this one...
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A new approach to the optimal focusing of array fields subject to arbitrary upper bounds is presented. The approach formulates the problem as the minimization of a linear function in a convex set. Unlike other approaches, this one guarantees the achievement of the global optimum by using local optimization techniques and can, moreover, deal with any convex constraint on the unknowns, such as near field constraints. Optimization is performed by two ad hoc developed solution algorithms, which exploit the geometrical characteristics of the problem at hand, thus leading to extremely effective and computationally efficient numerical codes. An extensive numerical analysis has been performed in all cases of linear, planar, and circular arc arrays. The enhanced performance of the proposed technique with respect to the solution algorithms available in the literature fully confirms the effectiveness of the approach.
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摘要 :
A new approach to the optimal focusing of array fields subject to arbitrary upper bounds is presented. The approach formulates the problem as the minimization of a linear function in a convex set. Unlike other approaches, this one...
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A new approach to the optimal focusing of array fields subject to arbitrary upper bounds is presented. The approach formulates the problem as the minimization of a linear function in a convex set. Unlike other approaches, this one guarantees the achievement of the global optimum by using local optimization techniques and can, moreover, deal with any convex constraint on the unknowns, such as near field constraints. Optimization is performed by two ad hoc developed solution algorithms, which exploit the geometrical characteristics of the problem at hand, thus leading to extremely effective and computationally efficient numerical codes. An extensive numerical analysis has been performed in all cases of linear, planar, and circular arc arrays. The enhanced performance of the proposed technique with respect to the solution algorithms available in the literature fully confirms the effectiveness of the approach
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Clinical trials have shown that hyperthermia is a potent adjuvant to conventional cancer treatments, but the temperatures currently achieved in the clinic are still suboptimal. Hyperthermia treatment planning simulations have pote...
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Clinical trials have shown that hyperthermia is a potent adjuvant to conventional cancer treatments, but the temperatures currently achieved in the clinic are still suboptimal. Hyperthermia treatment planning simulations have potential to improve the heating profile of phased-array applicators. An important open challenge is the development of an effective optimization procedure that enables uniform heating of the target region while keeping temperature below a threshold in healthy tissues. In this work, we analyzed the effectiveness and efficiency of a recently proposed optimization approach, i.e. focusing via constrained power optimization (FOCO), using 3D simulations of twelve clinical patient specific models. FOCO performance was compared against a clinically used particle swarm based optimization approach. Evaluation metrics were target coverage at the 25% iso-SAR level, target hotspot quotient, median target temperature (T50) and computational requirements. Our results show that, on average, constrained power focusing performs slightly better than the clinical benchmark (Delta T50 = +0.05 degrees C), but outperforms this clinical benchmark for large target volumes (>40 cm(3), Delta T50 = +0.39 degrees C). In addition, the results are achieved in a shorter time ( - 44%) and are repeatable because the approach is formulated as a convex optimization problem.
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