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一种利用少快拍数据的宽带干扰鲁棒性抑制算法 被引量:3
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作者 王昊 徐晓男 马启明 《电子与信息学报》 EI CSCD 北大核心 2019年第4期851-857,共7页
针对被动声呐对宽带干扰抑制的应用需求,该文提出一种利用少快拍数据的宽带干扰鲁棒性抑制算法。算法基于宽带干扰的预估方位,得到带宽内多频点叠加的导向互谱密度矩阵,以此估计出信号子空间,并采用投影法对单位向量修正,再逆转换得到... 针对被动声呐对宽带干扰抑制的应用需求,该文提出一种利用少快拍数据的宽带干扰鲁棒性抑制算法。算法基于宽带干扰的预估方位,得到带宽内多频点叠加的导向互谱密度矩阵,以此估计出信号子空间,并采用投影法对单位向量修正,再逆转换得到干扰导引向量估计。对所有待抑制的干扰重复上述步骤,得到干扰导引向量集,进而构造抑制矩阵。对阵元域数据处理得到剔除掉干扰成分的阵元数据,再进行空间处理即可得到最终的空间谱。理论分析及仿真、海试数据处理表明,算法可采用少快拍,甚至单快拍的频域数据进行处理。在目标运动、环境状态快速变化等不适宜时间积分的环境下依然具有良好性能,同时对空间处理面临的各类失配具有鲁棒性。 展开更多
关键词 声呐 宽带干扰 鲁棒性抑制 导向互谱密度矩阵 信号子空间投影法
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Experimental Measurement of the Generalized Stokes Parameters of a Radially Polarized Random Electromagnetic Beam
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作者 Yongxin Liu Songjie Luo +1 位作者 Jixiong Puri Zenghui Gao 《Journal of Electromagnetic Analysis and Applications》 2016年第6期109-114,共7页
Utilizing the Young’s double slits and Mach-Zehnder interferometer, we proposed an experimental method to measure the generalized Stokes parameters of a radially polarized random electromagnetic beam. After the parti... Utilizing the Young’s double slits and Mach-Zehnder interferometer, we proposed an experimental method to measure the generalized Stokes parameters of a radially polarized random electromagnetic beam. After the partially coherent beam propagating through the Young’s double slits, the interference fringe is obtained by the help of a Mach-Zehnder interferometer consisting of apertures, quarter-wave plates and polarizers. The electric cross-spectral density matrix is detected by the coherence degree of interference fringe and the density of each single slit. The generalized Stokes parameters can be obtained from the electric cross-spectral density matrix. This experiment measures the generalized Stokes parameters of the random electromagnetic beam successfully. The results show that the spectral degree of coherence for copolarized cases (xx and yy) is similar with that for cross-polaried cases (xy and yx) for the radially polarized random electromagnetic beam. This method will help us determine the change of the polarization and coherence of the light in propagation by detecting the change of the generalized Stokes parameters. 展开更多
关键词 Generalized Stokes Parameters Electric cross-spectral density matrix Young’s Double Slits Mach-Zehnder Interferometer Radially Polarized Stochastic Electromagnetic Beam
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Simulating Temporally and Spatially Correlated Wind Speed Time Series by Spectral Representation Method
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作者 Qing Xiao Lianghong Wu +1 位作者 Xiaowen Wu Matthias Rätsch 《Complex System Modeling and Simulation》 2023年第2期157-168,共12页
In this paper,it aims to model wind speed time series at multiple sites.The five-parameter Johnson mdistribution is deployed to relate the wind speed at each site to a Gaussian time series,and the resultant-Z(t)dimens... In this paper,it aims to model wind speed time series at multiple sites.The five-parameter Johnson mdistribution is deployed to relate the wind speed at each site to a Gaussian time series,and the resultant-Z(t)dimensional Gaussian stochastic vector process is employed to model the temporal-spatial correlation of mwind speeds at different sites.In general,it is computationally tedious to obtain the autocorrelation functions Z(t)(ACFs)and cross-correlation functions(CCFs)of Z(t),which are different to those of wind speed times series.In order to circumvent this correlation distortion problem,the rank ACF and rank CCF are introduced to Z(t)characterize the temporal-spatial correlation of wind speeds,whereby the ACFs and CCFs of can be analytically obtained.Then,Fourier transformation is implemented to establish the cross-spectral density matrix Z(t)mof,and an analytical approach is proposed to generate samples of wind speeds at different sites.Finally,simulation experiments are performed to check the proposed methods,and the results verify that the five-parameter Johnson distribution can accurately match distribution functions of wind speeds,and the spectral representation method can well reproduce the temporal-spatial correlation of wind speeds. 展开更多
关键词 multivariate wind speed time series rank autocorrelation function rank cross-correlation function cross-spectral density matrix five-parameter Johnson distribution
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