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Block diagram of the proposed technique for a 4-element array. The antennas are sampled in a nonsequential order and the information is digitized and transferred to a processing unit. 

Block diagram of the proposed technique for a 4-element array. The antennas are sampled in a nonsequential order and the information is digitized and transferred to a processing unit. 

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Phased arrays are a form of steerable antenna whose architecture makes the system complex and generally expensive. Their versatility and performance motivates the development of alternative structures which allow us to obtain simplified designs as powerful as the original approach but significantly cheaper. In this paper, a novel technique which co...

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... stands for the unit vector in the direction of the incoming signal and is the velocity of light in free space. According to the traditional phased array theory, it is possible to align the phase of signals received from each antenna, such that a constructive interference is produced. In other words, after alignment, all the signals present the same propagation delay. The economic sampling technique introduced in [7] is based on this principle, but instead of simultaneously sampling all the antennas, only one antenna is considered at a time. The idea is to sample the th antenna during a RF cycle, ( seconds), wait for seconds and continue with the th antenna, wait for seconds, and so forth. A scheme of the sampling process and its transmission to the processing unit is depicted in Fig. 2. The waiting time between the th and th antenna is computed as (2) where stands for the unit vector of the scanned angle. Equation (2) guarantees that the waiting time is positive but shorter than a RF cycle. The variable indicates the number of full cycles that should be subtracted or added in order to assure causality , as well as to avoid sampling the same cycle twice . As a result, cycles are lost between the th and th antenna if is positive, while we would need to wait extra full cycles if it is negative (a lost cycle does not trans- late into information loss since the transmitted signal can be re- covered by applying a LPF ...

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... As for the backtracking algorithm, it has proven reliable in solving CP problems [37] [38]. As a matter of fact, it has been successfully applied in electromagnetics to the sparse reconstruction of scatterers in through-the-wall imaging [39] and to the optimal signal sampling for bandwidth enhancement in phased arrays [40]. The main contributions of this paper are: (a) a formulation of the MCFC problem that allows one to adopt arbitrary metrics for dealing with any user-chosen array requirements; (b) the definition of a mathematical/theoretical framework suitable for an effective and reliable application of CP-based techniques to minimize the number of excitations to be reconfigured for recovering the pattern features of the original array; (c) the introduction of an innovative CP-based correction method that combines a ℓ 1 -norm relaxation of the ℓ 0 -norm with a backtracking strategy. ...
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Given an array with defective elements, failure correction (FC) aims at finding a new set of weights for the working elements so that the properties of the original pattern can be recovered. Unlike several FC techniques available in the literature, which update all the working excitations, the Minimum-Complexity Failure Correction (MCFC) problem is addressed in this paper. By properly reformulating the FC problem, the minimum number of corrections of the whole excitations of the array is determined by means of an innovative Compressive Processing (CP) technique in order to afford a pattern as close as possible to the original one (i.e., the array without failures). Selected examples, from a wide set of numerical test cases, are discussed to assess the effectiveness of the proposed approach as well as to compare its performance with other competitive state-of-the-art techniques in terms of both pattern features and number of corrections.
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Given an array with defective elements, failure correction (FC) aims at finding a new set of weights for the working elements so that the properties of the original pattern can be recovered. Unlike several FC techniques available in the literature, which update all the working excitations, the Minimum-Complexity Failure Correction (MCFC) problem is addressed in this paper. By properly reformulating the FC problem, the minimum number of corrections of the whole excitations of the array is determined by means of an innovative Compressive Processing (CP) technique in order to afford a pattern as close as possible to the original one (i.e., the array without failures). Selected examples, from a wide set of numerical test cases, are discussed to assess the effectiveness of the proposed approach as well as to compare its performance with other competitive state-of-the-art techniques in terms of both pattern features and number of corrections.