论文标题
在非高斯环境中的稳健半参数DOA估计
Robust Semiparametric DOA Estimation in non-Gaussian Environment
论文作者
论文摘要
采用了一般的非高斯半参数模型来表征通过线性阵列收集的测量向量，即\ \ textit {snapshots}。此外，将数据协方差矩阵的最近派生的\ textit {robust semiparametric效率} $ r $估计器被利用以实现音乐估算器的原始版本。通过比较源空间频率与相关的半参数随机cramér-rao bound（SSCRB）在估计源空间频率中比较其平方误差（MSE），从而研究了所得$ r $ r $ music算法的效率。
A general non-Gaussian semiparametric model is adopted to characterize the measurement vectors, i.e.\ the \textit{snapshots}, collected by a linear array. Moreover, the recently derived \textit{robust semiparametric efficient} $R$-estimator of the data covariance matrix is exploited to implement an original version of the MUSIC estimator. The efficiency of the resulting $R$-MUSIC algorithm is investigated by comparing its Mean Squared Error (MSE) in the estimation of the source spatial frequencies with the relevant Semiparametric Stochastic Cramér-Rao Bound (SSCRB).
