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Unitary Root MUSIC and Unitary MUSIC with Real-Valued Rank Revealing Triangular Factorization

机译:酉根音乐和酉音乐,具有实值等级揭示三角形分解

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This paper presents two methods to estimate the two dimensional (2-D) direction of arrival (DOA) for coherent and non-coherent sources. The proposed methods have many advantages over existing schemes. First, they construct the data from a single snapshot in a Toeplitz form, whose rank is directly related to the DOA of signals, whether the signals are coherent or not; hence, the algorithm does not require any forward/backward spatial smoothing. Second, the two proposed methods can rapidly estimate the 2-D DOAs of incident signals without requiring singular value decomposition (SVD) or eigenvalue decomposition (EVD), even in the case of coherent signals and a single snapshot. The two methods are: (1) orthogonal projection real-valued rank revealing QR factorization (OP-RRRQR), and (2) orthogonal projection real-valued rank revealing LU factorization (OP-RRRLU). The proposed methods reduce computational complexity and the cost at least by a factor of four by applying a unitary transformation, to the complex Toeplitz form to real data without forming the covariance matrix. The proposed algorithms employ the unitary root MUSIC and unitary MUSIC using cross array configuration to estimate the 2-D DOA azimuth and elevation angles without using the extensive 2-D MUSIC search. Hence, they can reduce the computational load and cost significantly and can be applied in real-time radar/sonar and commercial wireless systems. The simulation results show that the proposed algorithms can efficiently estimate the 2-D DOAs from different sources.
机译:本文呈现了两种方法来估计两维(2-D)到达的到达(DOA)方向,用于相干和非相干来源。所提出的方法对现有方案具有许多优点。首先,它们从一个快照的单个快照构成数据,其等级与信号的DOA直接相关,信号是否连贯;因此,该算法不需要任何前进/向后空间平滑。其次,两个所提出的方法可以快速估计入射信号的2-D DOAS,而不需要奇异值分解(SVD)或特征值分解(EVD),即使在相干信号和单一快照的情况下也是如此。这两种方法是:(1)正交投影实际值等级揭示QR分解(OP-RRRQR),和(2)正交投影实质值露出LU分解(OP-RRRLU)。所提出的方法通过将酉变换应用于复杂的Toeplitz表格到实际数据而不形成协方差矩阵来降低计算复杂度和至少四倍的成本。所提出的算法使用横阵配置的酉根音乐和酉音乐,以估计2-D DOA方位角和高度角度而不使用广泛的2-D音乐搜索。因此,它们可以显着降低计算负荷和成本,并且可以应用于实时雷达/声纳和商业无线系统。仿真结果表明,所提出的算法可以有效地估计来自不同来源的2-D DOA。

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