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Fast and accurate diagnosis of array failure is important for the maintenance of array antennas. Locations of failing elements are usually detected using near field data, which may be polluted by noises. Most existing diagnosis methods assume non-impulsive noise in the measurement data. However, the practical measurement environment may contain impulsive noises, which has not been considered in existing methods. This work proposes to impose a penalty function in the residual between the measured and recovered near field. The impulsive noise in the near field data can then be suppressed by using an appropriate function as the penalty function. Furthermore, minimum \ellp-norm is imposed on the excitation vector. The condition imposed on the noise and the minimum \ellp-norm constraint on the excitation vector constitutes an optimization problem, which is solved using the unsupervised support vector regression. The proposed method is more accurate than existing methods when impulsive noise presents in the near field data, and it is able to deal with a wide range of number of failing elements by adjusting the value of p. Numerical results are presented to show the advantages of the proposed method and to study the choice of p. [ABSTRACT FROM PUBLISHER]

Time-modulated arrays (TMAs) are antenna systems where the transmitted or received signal is modulated by periodic time pulses. Several strategies have been proposed for defining the characteristics of the pulse sequence to control the antenna radiation pattern starting from the hypothesis of ideal radio-frequency (RF) switches with instantaneous rise and fall time. In this paper, the use of switches having a non-null transition between the on and off state is taken into account and the impact on the radiation features is studied and verified through a set of numerical results also in comparative fashion with ordinary rectangular pulses. [ABSTRACT FROM PUBLISHER]

The need to reduce the number of active elements in radar arrays claims for developing new synthesis approaches able to reduce the control points, i.e., the number of transmit/receive modules (TRM) needed to fulfill the design constraints, is presented. As the large part of the TRM costs are related to the active parts (HPA—high power amplifier), a hybrid method for reducing the number of amplitude controls is proposed. This allow the design of new array architectural solutions where the scanning capabilities only rely on phase controls. [ABSTRACT FROM PUBLISHER]

Uniform amplitude sparse arrays have recently gained a renewed interest and a number of synthesis techniques, mainly based on global optimization algorithms, have been presented. In this paper, after a discussion about the expected characteristics of such arrays, a simple deterministic approach for the case of pencil beams patterns is proposed and discussed. The approach, which outperforms previous synthesis techniques, takes inspiration from existing (not well-known) density taper procedures to develop a two stages synthesis where the first step is solved in a new closed analytical form, while the second one just requires local refinements or fast 1-D optimizations. As a consequence, the proposed approach avoids the need of multidimensional global optimization procedures and the inherent possibly prohibitive computational costs. Notably the first step, which also exhibits an improved flexibility with respect to other analytical techniques, already outperforms previous approaches in a number of cases of interest. Several numerical results confirm the effectiveness and usefulness of the proposed tools. [ABSTRACT FROM AUTHOR]

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The problem of synthesizing "optimal" sum and difference patterns subject to arbitrary sidelobe bounds by means of a simple feeding network is dealt with. It is shown how a hybrid optimization procedure properly acting on both clustering into subarrays and excitations of these latter greatly improves performances of known feeding architectures with respect to existing procedures. Results of the proposed technique, which significantly outperform existing methods, renew the interest of these simple feeding architectures, and emphasize the effectiveness of this kind of hybrid procedures exploiting the convexity of the problem with respect to a part of the unknowns. [ABSTRACT FROM AUTHOR]

Most global optimization based synthesis procedures act in essentially the same way on all the involved variables. In this paper, it is theoretically discussed and numerically emphasized how explicit exploitation of the convexity of the problem with respect to a part of the degrees of freedom (when available) allows to achieve increased performances with respect to previous results, and to develop new interesting design solutions. Examples are presented for the synthesis of both sum and difference patterns by using nonuniformly spaced arrays and for the so called "optimal compromise amongst sum and difference patterns." Finally, the proposed approach is exploited in developing effective design solutions (based on the concept of interleaved arrays) to the problem of achieving very flexible antennas while using simple feeding networks. As an example, array antennas capable to radiate two different beams with individually steerable patterns, or to perform jammer rejection at the physical layer or even to realize a "flat-top" beam pattern are synthesized and presented [ABSTRACT FROM PUBLISHER]

A hybrid approach to the synthesis of excitations and locations of nonuniformly spaced arrays in order to achieve optimal focusing in any given direction is proposed and discussed. The approach takes definite advantage from the convexity of the problem with respect to excitation variables, and exploits a Simulated Annealing procedure as far as location variables are concerned. The corresponding synthesized patterns outperform previously known results in standard benchmark problems. [ABSTRACT FROM AUTHOR]