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Reduced-Complexity Direction of Arrival Estimation Using Real-Valued Computation with Arbitrary Array Configurations

机译:使用带有任意数组配置的实值计算的到达估计的降低复杂度方向

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A low-complexity algorithm is presented to dramatically reduce the complexity of the multiple signal classification (MUSIC) algorithm for direction of arrival (DOA) estimation, in which both tasks of eigenvalue decomposition (EVD) and spectral search are implemented with efficient real-valued computations, leading to about 75% complexity reduction as compared to the standard MUSIC. Furthermore, the proposed technique has no dependence on array configurations and is hence suitable for arbitrary array geometries, which shows a significant implementation advantage over most state-of-the-art unitary estimators including unitary MUSIC (U-MUSIC). Numerical simulations over a wide range of scenarios are conducted to show the performance of the new technique, which demonstrates that with a significantly reduced computational complexity, the new approach is able to provide a close accuracy to the standard MUSIC.
机译:提出了一种低复杂度算法,可显着降低用于到达方向(DOA)估计的多信号分类(MUSIC)算法的复杂度,其中特征值分解(EVD)和频谱搜索两个任务均以有效的实值实现计算,与标准MUSIC相比,可降低约75%的复杂度。此外,所提出的技术不依赖于阵列配置,因此适合于任意阵列几何形状,与包括unit一声MUSIC(U-MUSIC)的大多数最新的unit一估计器相比,它显示出显着的实现优势。进行了各种场景的数值模拟,以显示该新技术的性能,这表明在显着降低计算复杂度的情况下,该新方法能够提供与标准MUSIC接近的准确性。

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