针对色噪声下基于差分去噪的宽带相干信号波达方向(direction of arrival,DOA)估计方法对相干信源数有限制的问题,提出一种基于噪声圆形特性去噪和Toeplitz矩阵重构的估计算法。首先,对接收到的信号求取协方差矩阵,利用噪声的圆形特性...针对色噪声下基于差分去噪的宽带相干信号波达方向(direction of arrival,DOA)估计方法对相干信源数有限制的问题,提出一种基于噪声圆形特性去噪和Toeplitz矩阵重构的估计算法。首先,对接收到的信号求取协方差矩阵,利用噪声的圆形特性消除噪声。为达到对协方差矩阵进行Toeplitz矩阵重构的要求,通过协方差矩阵相乘来构造新的数据协方差矩阵。然后,通过Toeplitz矩阵重构来解相干。最后,利用旋转子空间算法准则构造聚焦矩阵,使用传播算子算法实现DOA估计。理论分析及仿真实验验证了该算法的有效性,该算法对相干信源数的奇偶没有限制,同时该算法也适用于高斯白噪声下宽带相干信号DOA估计的场景。展开更多
To cope with the scenario where both uncorrelated sources and coherent sources coexist, a novel algorithm to direction of arrival （DOA） estimation for symmetric uniform linear array is presented. Under the condition...To cope with the scenario where both uncorrelated sources and coherent sources coexist, a novel algorithm to direction of arrival （DOA） estimation for symmetric uniform linear array is presented. Under the condition of stationary colored noise field, the algorithm employs a spatial differencing method to eliminate the noise covariance matrix and uncorrelated sources, then a Toeplitz matrix is constructed for the remained coherent sources. After preprocessing, a propagator method （PM） is employed to find the DOAs without any eigendecomposition. The number of sources resolved by this approach can exceed the number of array elements at a lower computational complexity. Simulation results demonstrate the effectiveness and efficiency of the proposed method.展开更多
文摘针对色噪声下基于差分去噪的宽带相干信号波达方向(direction of arrival,DOA)估计方法对相干信源数有限制的问题,提出一种基于噪声圆形特性去噪和Toeplitz矩阵重构的估计算法。首先,对接收到的信号求取协方差矩阵,利用噪声的圆形特性消除噪声。为达到对协方差矩阵进行Toeplitz矩阵重构的要求,通过协方差矩阵相乘来构造新的数据协方差矩阵。然后,通过Toeplitz矩阵重构来解相干。最后,利用旋转子空间算法准则构造聚焦矩阵,使用传播算子算法实现DOA估计。理论分析及仿真实验验证了该算法的有效性,该算法对相干信源数的奇偶没有限制,同时该算法也适用于高斯白噪声下宽带相干信号DOA估计的场景。
基金the National Natural Science Foundation of China (60601016)
文摘To cope with the scenario where both uncorrelated sources and coherent sources coexist, a novel algorithm to direction of arrival （DOA） estimation for symmetric uniform linear array is presented. Under the condition of stationary colored noise field, the algorithm employs a spatial differencing method to eliminate the noise covariance matrix and uncorrelated sources, then a Toeplitz matrix is constructed for the remained coherent sources. After preprocessing, a propagator method （PM） is employed to find the DOAs without any eigendecomposition. The number of sources resolved by this approach can exceed the number of array elements at a lower computational complexity. Simulation results demonstrate the effectiveness and efficiency of the proposed method.
