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Low-angle tracking of two objects in a three-dimensional beamspace domain

机译:三维束空间域中两个对象的低角度跟踪

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摘要

Among various low-angle tracking methods, the three-dimensional beamspace domain maximum likelihood (3-D BDML) estimation proposed by Zoltowski is a computationally attractive and optimal method that can be processed in the reduced beamspace domain. However, the estimation performance of 3-D BDML deteriorates in the presence of interference or an additional target, especially at low altitudes, because the dimension of the signal and noise exceeds the dimension provided by the three beams. This study proposes a new low-angle tracking method for two objects in a 3-D beamspace domain using a linearly constrained adaptive array. The increased signal dimension owing to the interference or the additional target is reduced in the beamspace domain by using the beamforming weight that is designed to remove the largest principal component in the covariance matrix. Numerical simulation results are provided to show the estimation performance of the proposed method.
机译:在各种低角度跟踪方法中,Zoltowski提出的三维波束空间域最大似然(3-D BDML)估计是一种在计算上有吸引力的最佳方法,可以在缩小的波束空间域中进行处理。但是,由于信号和噪声的大小超过了三个波束提供的大小,因此在存在干扰或存在其他目标的情况下,尤其是在低海拔地区,3-D BDML的估计性能会下降。这项研究提出了一种新的低角度跟踪方法,该方法使用线性约束自适应阵列对3-D束空间域中的两个对象进行跟踪。通过使用设计用于去除协方差矩阵中最大主成分的波束成形权重,可以在波束空间域中减少由于干扰或附加目标而导致的信号尺寸增大。数值仿真结果表明了该方法的估计性能。

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