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首页> 外文期刊>IEEE communications letters >A New Approach to Achieve a Trade-Off Between Direction-of-Arrival Estimation Performance and Computational Complexity
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A New Approach to Achieve a Trade-Off Between Direction-of-Arrival Estimation Performance and Computational Complexity

机译：一种在抵达方向估算性能与计算复杂性之间实现权衡的新方法

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摘要

The multiple signal classification (MUSIC) algorithm is a promising method for the plethora of problems related to the direction-of-arrival (DOA) estimation. Conventionally, this approach uses the whole sensor array observations to obtain the signal or noise subspace, which consequently leads to a huge computational burden. In this letter, to circumvent this problem, we make a significant modification to the traditional MUSIC algorithm. First, we compute only two sub-matrices of the sample covariance matrix (SCM) exploiting the Nystrom method avoiding its complete calculation. These matrices can be used to construct an accurate noise subspace without calculating the SCM and its eigenvalue decomposition (EVD). Furthermore, to have a uniform DOA estimation, we modify the classical ULA by displacing two antenna elements from both the ends of the array to a top and a bottom of the array axis. This unique structure improves the estimation of DOAs near and at the array end fires. Several numerical results are included to confirm the efficacy of the new method.
机译：多信号分类（音乐）算法是一种有希望的方法，用于与到达方向（DOA）估计有关的血清问题。传统上，这种方法使用整个传感器阵列观察来获得信号或噪声子空间，从而导致巨大的计算负担。在这封信中，为了避免这个问题，我们对传统音乐算法进行了重大修改。首先，我们仅计算用于利用其完全计算的NYSTROM方法的样本协方差矩阵（SCM）的两个子矩阵。这些矩阵可用于构建精确的噪声子空间，而无需计算SCM及其特征值分解（EVD）。此外，为了具有统一的DOA估计，我们通过将两个天线元件从阵列的两端移位到阵列轴的顶部和底部来修改经典ULA。这种独特的结构改善了近距离和阵列端火附近的DOA的估计。包括几个数值结果以确认新方法的功效。

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