为提高空间相关噪声场中的目标方位估计性能，提出一种基于空时相关阵联合块对角化的子空间方位估计算法．具体利用Jacobi旋转矩阵法对一组空时相关阵联合近似对角化，用联合对角化特征向量矩阵和特征值修正MUSIC（Multiple Signal Clas...为提高空间相关噪声场中的目标方位估计性能，提出一种基于空时相关阵联合块对角化的子空间方位估计算法．具体利用Jacobi旋转矩阵法对一组空时相关阵联合近似对角化，用联合对角化特征向量矩阵和特征值修正MUSIC（Multiple Signal Classification）等子空间算法。理论和仿真结果表明，在非相关噪声场中，基于联合对角化的子空间算法性能与常规子空间算法基本一致：而在相关噪声场中，联合对角化特征向量法能显著减小方位估计方差，提高估计性能。展开更多
Noise level in a marine environment has raised extensive concern in the scientific community.The research is carried out on i4 Ocean platform following the process of ocean noise model integrating,noise data extractin...Noise level in a marine environment has raised extensive concern in the scientific community.The research is carried out on i4 Ocean platform following the process of ocean noise model integrating,noise data extracting,processing,visualizing,and interpreting,ocean noise map constructing and publishing.For the convenience of numerical computation,based on the characteristics of ocean noise field,a hybrid model related to spatial locations is suggested in the propagation model.The normal mode method K/I model is used for far field and ray method CANARY model is used for near field.Visualizing marine ambient noise data is critical to understanding and predicting marine noise for relevant decision making.Marine noise map can be constructed on virtual ocean scene.The systematic marine noise visualization framework includes preprocessing,coordinate transformation interpolation,and rendering.The simulation of ocean noise depends on realistic surface.Then the dynamic water simulation gird was improved with GPU fusion to achieve seamless combination with the visualization result of ocean noise.At the same time,the profile and spherical visualization include space,and time dimensionality were also provided for the vertical field characteristics of ocean ambient noise.Finally,marine noise map can be published with grid pre-processing and multistage cache technology to better serve the public.展开更多
文摘为提高空间相关噪声场中的目标方位估计性能，提出一种基于空时相关阵联合块对角化的子空间方位估计算法．具体利用Jacobi旋转矩阵法对一组空时相关阵联合近似对角化，用联合对角化特征向量矩阵和特征值修正MUSIC（Multiple Signal Classification）等子空间算法。理论和仿真结果表明，在非相关噪声场中，基于联合对角化的子空间算法性能与常规子空间算法基本一致：而在相关噪声场中，联合对角化特征向量法能显著减小方位估计方差，提高估计性能。
基金supported by the Global Change and Air-Sea Interaction Project (GASI-03-01-01-09)the National Natural Science Foundation of China under Grant No.61170106+1 种基金the Project funded by China Postdoctoral Science Foundation under Grant No.2015M571993Qingdao Postdoctoral Application Research Funded Project
文摘Noise level in a marine environment has raised extensive concern in the scientific community.The research is carried out on i4 Ocean platform following the process of ocean noise model integrating,noise data extracting,processing,visualizing,and interpreting,ocean noise map constructing and publishing.For the convenience of numerical computation,based on the characteristics of ocean noise field,a hybrid model related to spatial locations is suggested in the propagation model.The normal mode method K/I model is used for far field and ray method CANARY model is used for near field.Visualizing marine ambient noise data is critical to understanding and predicting marine noise for relevant decision making.Marine noise map can be constructed on virtual ocean scene.The systematic marine noise visualization framework includes preprocessing,coordinate transformation interpolation,and rendering.The simulation of ocean noise depends on realistic surface.Then the dynamic water simulation gird was improved with GPU fusion to achieve seamless combination with the visualization result of ocean noise.At the same time,the profile and spherical visualization include space,and time dimensionality were also provided for the vertical field characteristics of ocean ambient noise.Finally,marine noise map can be published with grid pre-processing and multistage cache technology to better serve the public.
