摘要:
针对低信噪比条件下多输入多输出声呐受对称噪声分量影响导致测向性能降低的情况,提出了一种基于协方差矩阵重构方法的波达方向估计算法。首先,将噪声场分为对称噪声和非对称噪声两部分,利用协方差矩阵虚部与对称信号无关的性质,去掉协方差矩阵的实部来降低对称噪声对目标波达方向估计精度的影响,采用降维转换方法和矩阵虚部置换原理重构协方差矩阵的实部,避免了双频谱的干扰。然后利用Toeplitz方法对重构的协方差矩阵进行解相干修正,通过奇异值分解获得噪声子空间,最后对目标的波达方向进行估计,可实现微弱信号的准确测向。理论分析和实验结果表明,该方法明显抑制了对称噪声,提高了目标的波达方向估计性能,具有运算速度快、自由度高和目标分辨力强的特点。
Abstract:
By studying the influence of symmetrical noise component on multiple-input multiple-output sonar's DOA (Direction Of Arrival) estimation under the condition of low signal noise ratio, a DOA estimation algorithm based on covariance matrix reconstruction method is proposed. Firstly, the noise field is decomposed into symmetrical noise field and asymmetrical noise field, we utilize symmetry property of colored noise matrix and the feature that the imaginary part of covariance matrix has no relation with the symmetry noise, remove the real part of covariance matrix to avoid the influence of colored noise on DOA estimation accuracy. By subtracting the imaginary part of covariance matrix and reducing the dimension, the real part of covariance matrix is reconstructed, which helps to avoid the bilateral spectrum interference. Thereafter, Toeplitz method is applied for the covariance matrix decorrelation amendment, a noise subspace is formed by Singular Value Decomposition (SVD), Finally, we can estimate the DOA of target signal. Both theoretical analysis results and numerical simulation results verify that this algorithm suppress symmetrical noise obviously, the estimation performance of targets azimuth is improved. This method has the characteristics of fast calculation, higher degrees of freedom and stronger target resolution.
百度学术
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