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Azimuth and elevation angle estimation with no failure and no eigen decomposition

机译:无故障且无特征分解的方位角和仰角估计

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Recently, Wu et al. proposed a scheme for two-dimensional direction of arrival angle estimation for azimuth and elevation angles, using the propagator method. An advantage of this method over the classical subspace based algorithms, such as ESPRIT and MUSIC, is that it does not apply any eigenvalue decomposition (EVD) to the cross spectral matrix or singular value decomposition (SVD) to the received data. This significantly reduces the computational complexity, compared to the EVD and SVD. However, Wu's method has some drawbacks, such as pair matching between the azimuth and elevation angle estimations for multiple different sources. Furthermore, Wu's method has an estimation failure problem in the range of practical mobile elevation angles. The objectives of this paper are two-fold: (1) to overcome these two problems with less arithmetic operation counts than Wu used; and (2) to improve the performance significantly. To achieve these objectives, we propose an antenna array configuration which avoids these problems. Simulation results verify that the proposed scheme can remove these problems and give much better performance. (c) 2005 Elsevier B.V. All rights reserved.
机译:最近,吴等。提出了一种使用传播子方法估计方位角和仰角的二维到达角方向的方案。与传统的基于子空间的算法(例如ESPRIT和MUSIC)相比,此方法的优点是它不会对交叉谱矩阵应用任何特征值分解(EVD)或对接收到的数据应用奇异值分解(SVD)。与EVD和SVD相比,这大大降低了计算复杂度。然而,Wu的方法有一些缺点,例如,针对多个不同源的方位角和仰角估计之间的配对匹配。此外,Wu的方法在实际移动仰角范围内存在估计失败的问题。本文的目的有两个:(1)以比Wu少的算术运算数来克服这两个问题; (2)显着提高性能。为了实现这些目标,我们提出一种避免这些问题的天线阵列配置。仿真结果验证了所提方案可以消除这些问题,并具有更好的性能。 (c)2005 Elsevier B.V.保留所有权利。

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