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This paper presents a novel array response control algorithm and its application to array pattern synthesis. The proposed algorithm considers how to flexibly and precisely adjust the array responses at multiple points, on the basis of one given weight vector. With the principle of adaptive beamforming, it is shown that the optimal weight vector for array response control can be equivalently obtained with a different manner, in which a linear transformation is conducted on the quiescent weight. This new strategy is utilized to realize multi-point precise array response control from one given weight vector, and it obtains a closed-form solution. A careful analysis shows that the response levels at given points can be independently, flexibly and accurately adjusted by simply varying the parameter vector, and that the uncontrolled region remains almost unchanged. By applying the proposed algorithm, an effective pattern synthesis approach is devised. Simulation results are provided to demonstrate the performance of the proposed algorithm.
In this paper, the problem of how to optimally and precisely control array response levels is addressed. By using the concept of the optimal weight vector from the adaptive array theory and adding virtual interferences one by one, the change rule of
In this paper, the optimal and precise array response control (OPARC) algorithm proposed in Part I of this two paper series is extended from single point to multi-points. Two computationally attractive parameter determination approaches are provided
In this work, we tackle the problem of hyperspectral (HS) unmixing by departing from the usual linear model and focusing on a Linear-Quadratic (LQ) one. The proposed algorithm, referred to as Successive Nonnegative Projection Algorithm for Linear Qua
Decision forests, including Random Forests and Gradient Boosting Trees, have recently demonstrated state-of-the-art performance in a variety of machine learning settings. Decision forests are typically ensembles of axis-aligned decision trees; that i
In this paper, we propose a fast method for array response adjustment with phase-only constraint. This method can precisely and rapidly adjust the array response of a given point by only varying the entry phases of a pre-assigned weight vector. We sh