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Grid-less coherent DOA estimation based on fourth-order cumulants with Gaussian coloured noise

机译:基于高斯彩色噪声的四阶累积物的网格相干的DOA估计

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This study investigates the continuous coherent direction-of-arrival (DOA) estimation, and concentrated on developing grid-less sparsity-based methods to Gaussian coloured noise environment. The noise component is greatly suppressed by applying fourth-order cumulants (FOC) due to its blind property to additive Gaussian noise. Two grid-less sparse models are designed separately. The first sparse representation model is built based on the simplified FOC vector, which would effectively reduce the computational complexity. Then the dual atomic norm minimisation algorithms are applied to solve the basis mismatch problem and improve the estimation accuracy. Additionally, a Toeplitz matrix based on FOC vector is constructed. The second sparse model based on this Toeplitz FOC matrix is proposed to implement array aperture extension, which can break through the restriction of maximum signal number and improve resolution. The proposed methods can handle the coherent signals and do not require the signal number as a prior. Numerical simulations demonstrate the outperformance of the proposed methods in estimation precision, computational cost and robustness to coloured noise.
机译:本研究调查了连续的抵达方向(DOA)估计,并集中在高斯彩色噪声环境中开发基于网格的基于稀疏性的方法。由于其盲目的属性来施加四阶累积物(FOC),大大抑制了噪声分量,以对加高斯噪声来施加四阶累积物(FOC)。两种稀疏型号分别设计。基于简化的FOC向量构建第一稀疏表示模型,这将有效地降低计算复杂度。然后应用双原子规范最小化算法来解决基础错配问题并提高估计精度。另外,构建基于FOC向量的Toeplitz矩阵。提出了基于该Toeplitz Foc矩阵的第二稀疏模型来实现阵列孔径扩展,可以通过最大信号数的限制来分离,并提高分辨率。所提出的方法可以处理相干信号,并且不需要先前的信号编号。数值模拟证明了所提出的方法在估计精度,计算成本和鲁棒性对彩色噪声的表现。

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