射电天文研究组知识库

射电天文观测数据受无线电的影响日益严重。因此,射频干扰(Radio Frequencv Inter ference,RFI)消除已经成为信号处理流程中不可或缺的一步。考虑了自适应阵列信号处理中的移动干扰源的消除问题,对于阵列天线望远镜而言,射频干扰消除可以通过采样协方差矩阵在空域实施处理。在很多应用场景中,可得到的零点深度受限于协方差矩阵的估计误差,进而影响干扰子空间的估计精度。方法应用了一种多项式模型以跟踪阵列协方差矩阵随时间的变化,消除干扰子空间的估计误差,提高干扰消除性能。最后通过仿真对比了传统的子空间投影(Subspace Projection,SP)算法和基于多项式模型的子空间投影(Polynomilaugmented Subspace Projection,PSP)算法,仿真结果证明了所提方法的有效性。

Radio astronomical data are increasingly corrupted by human telecommunication activities. Therefore, Radio Frequency Interference (RFI) mitigation becomes an important step in the data processing flow. This paper considers the problem of adaptive array processing for interference canceling to drive nulls in a moving interference environment. As to the telescopes based on antenna array, RFI mitigation can be
conducted in spatial domain using the sampled covariance matrix. In many practical scenarios, the achievable null depth is limited by covariance matrix estimation error which leads to poor identification of the interference subspace. We pay attention to the particularly troublesome cases of relatively rapid interference motion. A polynomial-based model is incorporated in the proposed algorithm to track changes in the array covariance matrix over time, mitigate interference subspace estimation errors, and improve canceler performance. Performance for conventional subspace projection (SP) is compared with polynomial-augmented SP using simulation. The simulation results validate the effectiveness of the proposed algorithm.