摘要
在空间弱信号DOA正确估计问题的研究中,针对强弱信号并存时弱信号波达方向(direction of arrival,DOA)难以准确估计的问题,提出了一种强信号背景下弱信号DOA估计新方法,首先估计阵列接收数据协方差矩阵,利用协方差矩阵特征值梯度变化不同的特点估计出强信号子空间;然后将强信号的子空间正交化后并入噪声子空间,形成扩展子空间;同时构建新的导向矢量,利用常规多信号分类(multiple signalclassification,MUSIC)算法得到弱信号的DOA估计。算法无需已知强信号个数及DOA,通过扩展噪声子空间抑制强信号谱峰,具有更高的强弱信号分辨率。仿真结果验证了改进方法的可行性和有效性,可为正确估计弱信号DOA提供了依据。
For the problem of the direction of arrival estimation of the weak signals in the presence of the strong signals, a new DOA estimation approach for weak signals was proposed. First, the subspace of strong signals were estimated through the eigenvalues＇ gradient change of the covariance matrix, then the traditional noise subspace was extended by adding in the orthogonal subspace of strong signals. A new steering vector was constructed, then the MU- SIC algorithm was applied, and the DOA of weak signals were obtained. The approach does not need the numbers and the DOA of strong signals, attenuates the peaks of strong signals in spatial spectrum by extending the noise subspace, and has better performance of strong and weak signals resolution. Computer simulation demonstrates its effectiveness and feasibility.
出处
《计算机仿真》
CSCD
北大核心
2014年第7期165-169,共5页
Computer Simulation
关键词
强信号
波达方向估计
噪声子空间
协方差矩阵
Strong signals
Direction of arrival estimation
Noise subspace
Covariancc matrix
