中文摘要：

针对在低频信道下多天线信号检测问题,提出一种新型的多维大气噪声模型的参数估计算法.通过推导贝叶斯模型,设计马尔科夫链蒙特卡罗算法,并在迭代中采用Gibbs和Metropolis-Hasting混合抽样的方法,能够有效估计出多维噪声模型的参数.多维大气噪声模型建模为应用广泛的亚高斯分布.仿真实验表明：该算法能迅速收敛于真实值,估计器相对误差能被有效控制,且易于并行实现.

英文摘要：

A novel algorithm to estimate the multivariate atmospheric noise model was proposed to detect signals over low frequency channels with multiple antennas.A Markov chain Monte Carlo algorithm was developed to effectively estimate the parameters of multivariate atmospheric noise model through the Bayesian inference,in which both the Gibbs sampler and the Metropolis-Hasting algorithm were employed.The multivariate atmosperic noise was modeled as the sub-Gaussian distribution.The simulation results show that the proposed estimators converge to the true values rapidly and the relative errors can be curbed effectively,which is suited for the parallel implementation.