电讯技术2016，Vol.56Issue(12)：1352-1358,7.DOI:10.3969/j.issn.1001-893x.2016.12.009
基于群Monte Carlo的大气噪声二维模型参数估计
Parameter Estimation of 2-D Model for Atmospheric Noise Based on Population Monte Carlo Algorithm
摘要
Abstract
In order to solve the problem that includes the parameter estimation of the multi-dimensional non-Gaussian noise model with multi-antenna optimum receiver,a method is proposed to estimate parame-ters of two-dimensional(2-D) atmospheric noise model based on population Monte Carlo(PMC). Both the Markov chain Monte Carlo algorithm and optimized sampling importance resampling method are used to achieve the global optimal parameter estimation of the multi-dimensional non-Gaussian noise model. Be-sides,the corresponding algorithm is designed. In consideration of the algorithm requirement for low compu-tational complexity,core computation is designed for fine grain parallelization based on the graphics pro-cessing unit( GPU) . It improves the algorithm efficiency greatly,and can satisfy the need for real-time pro-cessing. The simulation results show that the presented algorithm possesses the characteristics of high pre-cision and fast convergent iteration. The relative error is generally smaller than 0. 02,and the maximum rel-ative error is smaller than 0. 05. Compared with traditional computing method,the presented method can improve the computing efficiency greatly. And it can fully satisfy the real-time computation in low frequen-cy communication systems.关键词
低频通信/非高斯噪声参数估计/二维大气噪声模型/Class A 模型/群蒙特卡洛/并行计算Key words
low frequency communication/non-Gaussion noise parameter estimation/2-D atmospheric noise model/Class A model/population Mentor Carlo/parallel computing分类
信息技术与安全科学引用本文复制引用
应文威,张学波,刘旭波,李成军..基于群Monte Carlo的大气噪声二维模型参数估计[J].电讯技术,2016,56(12):1352-1358,7.基金项目
国家自然科学基金资助项目(41304015) （41304015）
装备预研基金项目(9140C290401150C29132) （9140C290401150C29132）
