【摘要】 随着阵列理论的发展和应用 ,单通道接收机相对于多通道接收机显示出独特的优越性。此中协方差矩阵的恢复成为一个关键问题。本文针对这一问题 ,利用在不相关信号源条件下均匀线阵协方差矩阵具有的 Toeplitz和 Hermite性质 ,在理论上最少条件数的意义下 ,给出了协方差矩阵的随机权恢复方法 ,并进一步将此思想应用于稀布线阵 ,给出了在极限意义下的最少条件数的协方差矩阵恢复方法。仿真实验表明 ,本文所提的最少条件数的随机权方法具有很强的可操作性 ,说明了单通道接收机协方差矩阵的随机权恢复方法相对于现有方法具有所需条件数少和灵活方便的优点。更多还原

【Abstract】 With the development and application of the array theory, single receiver takes more priorities over multiple receivers, and in this application, how to recover or estimate the covariance matrix becomes more important. According to the process of spatial spectrum estimation and direction finding via a single receiver, a method for covariance matrix recovery is proposed, using the least number of conditions and the uniform arrays′ covariance matrix′s Toepletz-Hermite properties, and considering the uncorrelated source. Then, exerting this thought into sparse array, this paper gives the corresponding recovery approach. Experimental results show the operability of this random weight method with minimal conditions. Comparing to existed method to recover the covariance matrix, it has the advantage of least condition required and is easy to be controlled theoretically and practically.更多还原