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3D-0MP and 3D-F0MP algorithms for DOA estimation

机译：用于DOA估计的3D-0MP和3D-F0MP算法

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Adaptive antennas and antenna array processing have vital effects on enhancing the performance of wireless communication networks. One of the most significant applications of adaptive antenna systems is the Direction of Arrival (DOA) detection. Several schemes have been proposed in the literature for DOA estimation in two-dimensional space. Among them, Orthogonal Matching Pursuit (OMP) algorithm provides several advantages in comparison to other schemes. The OMP algorithm reduces complexity and improves resolution of detection. Furthermore, in this algorithm, the number of signal emitters is not required to be known. In this paper, we extend the OMP algorithm and propose Three Dimensional OMP (3D-OMP) scheme for DOA estimation in three dimensional space. We provide a redundant dictionary for 3D-OMP scheme by employing azimuth and elevation angles. Simulation results show the high performance of the 3D-OMP algorithm when the signal to noise ratio is higher than - 10dB. Moreover, the 3D-OMP algorithm has a high efficiency in detecting multiple signal sources, simultaneously. Then, we evaluate the accuracy of the estimated directions by the 3D-OMP algorithm via comparing the variance of estimation error with the Cramer-Rao bound. Nevertheless, DOA estimation by the 3D-OMP algorithm has a substantial challenge where it cannot distinguish between two adjacent signal sources. To resolve this challenge, we propose Three Dimensional Focused Orthogonal Matching Pursuit (3D-FOMP) algorithm. The 3D-FOMP algorithm is an improved version of the 3D-OMP algorithm. It can detect two adjacent signal sources when the beam former has a single peak corresponding to a direction between right directions. In addition, we show the 3D-OMP and 3D-FOMP algorithms have lower complexities in comparison to the 3D-MUSIC and 3D-ESPRIT schemes when Root Mean Square Error (RMSE) 0.3 degrees. This accuracy is persuasive for most applications. Moreover, simulation results show the capability of the 3D-FOMP algorithm to detect adjacent signal sources and it outperforms the 3D-OMP, 3D-MUSIC and 3D-ESPRIT algorithms for all values of signal to noise ratio. (C) 2018 Elsevier B.V. All rights reserved.
机译：自适应天线和天线阵列处理对增强无线通信网络的性能具有至关重要的作用。自适应天线系统最重要的应用之一是到达方向（DOA）检测。文献中已经提出了几种用于二维空间中DOA估计的方案。其中，与其他方案相比，正交匹配追踪（OMP）算法具有许多优势。 OMP算法降低了复杂度并提高了检测分辨率。此外，在该算法中，不需要知道信号发射器的数量。在本文中，我们扩展了OMP算法，并提出了三维OMP（3D-OMP）方案，用于在三维空间中进行DOA估计。我们通过使用方位角和仰角为3D-OMP方案提供了冗余字典。仿真结果表明，当信噪比高于-10dB时，3D-OMP算法具有高性能。此外，3D-OMP算法在同时检测多个信号源方面具有很高的效率。然后，我们通过将估算误差的方差与Cramer-Rao边界进行比较，来评估3D-OMP算法估算的方向的准确性。然而，通过3D-OMP算法进行的DOA估计存在很大的挑战，即无法区分两个相邻的信号源。为了解决这一挑战，我们提出了三维聚焦正交匹配追踪（3D-FOMP）算法。 3D-FOMP算法是3D-OMP算法的改进版本。当波束形成器具有对应于右方向之间的方向的单个峰时，它可以检测到两个相邻的信号源。此外，我们显示，当均方根误差（RMSE）> 0.3度时，与3D-MUSIC和3D-ESPRIT方案相比，3D-OMP和3D-FOMP算法具有较低的复杂度。对于大多数应用而言，这种准确性很有说服力。此外，仿真结果显示了3D-FOMP算法检测相邻信号源的能力，并且在所有信噪比值方面都优于3D-OMP，3D-MUSIC和3D-ESPRIT算法。 （C）2018 Elsevier B.V.保留所有权利。

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