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Removing grating lobes in sparse sensor arrays with a nonlinear approach

机译:用非线性方法消除稀疏传感器阵列中的光栅波瓣

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Two of the most important criteria for a sensor array beam-pattern are beamwidth and side-lobe level. A narrower beamwidth means a better angular resolution and well separation of close sources. The beamwidth of a sensor array is directly proportional to array aperture, the beamwidth gets narrower as array aperture increases. However, increase in array aperture means increase in number of used sensors due to Nyquist spatial rate and this means increase in cost and computational load. Therefore, sparse arrays which violate Nyquist spatial rate are used. To cancel grating lobes occurred due to violation of Nyquist rate a weight optimization is implemented. In this paper, an approach which does not need weight optimization for grating lobe cancellation is presented. This method is inspired from nonlinear apodization (windowing) method. The necessary information to cancel grating lobes is obtained from a sub-array contained in the sparse array and this sub-array obeys Nyquist spatial rate.
机译:传感器阵列波束模式的两个最重要标准是波束宽度和旁瓣电平。较窄的波束宽度意味着更好的角度分辨率和近距离光源的良好分离。传感器阵列的束宽与阵列孔径成正比,随着阵列孔径的增加,束宽变窄。然而,阵列孔径的增加意味着由于奈奎斯特空间速率而使使用的传感器的数量增加,这意味着成本和计算负荷的增加。因此,使用了违反奈奎斯特空间速率的稀疏数组。为了消除由于违反奈奎斯特速率而产生的光栅波瓣,实施了权重优化。本文提出了一种无需权重优化即可消除光栅波瓣的方法。该方法的灵感来自于非线性切趾(窗口化)方法。从稀疏阵列中包含的子阵列中获得消除光栅波瓣的必要信息,并且该子阵列服从奈奎斯特空间速率。

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