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DOA Estimation with Co-Prime Arrays Based on Multiplicative Beamforming

机译:基于乘法波束成形的共序阵列进行DOA估计

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Co-Prime Sensor Array (CSA) is a form of sparse sensing has been recently introduced as an effective configuration in direction of arrival (DOA) estimation. Since the intercessor spacing is greater than the one-half wavelength, the CSA has the drawback of generating grating lobes in power pattern. To mitigate this problem, we propose a novel method based on digital beamforming at sub-array level using product processor. In this paper the main goal is nulling the grating lobes with known directions. Hence, the angular location of the grating lobes in the CSA subarrays are analytically extracted and trimmed so that by using a product processor, the grating lobes of the considered sub-array removed by nulls of the other sub-array. The performance of the proposed method in co-prime sensor array with N=N1+N2-1 sensors is compared to a fully populated uniform linear array (full ULA) with M=N1N2 physical sensors. The results of simulations demonstrate that the array power pattern obtained by the proposed method is better than the previous methods, so called product and min processors.
机译:共激素传感器阵列(CSA)是稀疏感测的形式,最近被引入到达方向(DOA)估计方向上的有效配置。由于晶体间隔大于半波长,因此CSA具有在功率图案中产生光栅叶片的缺点。为缓解此问题,我们使用产品处理器提出基于子阵列电平的数字波束形成的新方法。在本文中,主要目标是具有已知方向的光栅裂片。因此,在CSA子阵列中的光栅叶片的角度位置被分析并修整,使得通过使用产品处理器,所考虑的子阵列的光栅凸栅通过其他子阵列的空而被移除。具有n = n的共素传感器阵列中提出的方法的性能 1 + N. 2-1 与M = N的完全填充的均匀线性阵列(全ULA)进行比较。 1 N 2 物理传感器。仿真结果表明,通过所提出的方法获得的阵列功率模式优于先前的方法,所以称为产品和最小处理器。

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