Scattering Center Modeling Using Adaptive Segmental Compressive Sampling  

作　　者：Qifeng Li Kunyi Guo Jiaxin Wang Xinqing Sheng Tianshu Liu 

机构地区：[1]Center for Electromagnetic Simulation,School of Information and Electronics,Beijing Institute of Technology [2]Science and Technology on Special System Simulation Laboratory,Beijing Simulation Center

出　　处：《Journal of Beijing Institute of Technology》2017年第4期484-493,共10页北京理工大学学报（英文版）

基　　金：Supported by the National Natural Science Foundation of China(61421001,61471041,61671059)

摘　　要：In order to deal with aliasing distortions of Doppler frequencies shown in time-frequency representation（ TFR） with aspect undersampling,an approach using adaptive segmental compressive sampling according to the aspect dependencies of the scattering centers is proposed. The random noise problem induced by compressive sampling is solved by employing a series of signal processing techniques of filtering,image transformation and Hough Transform. Three examples are presented to verify the effectiveness of this approach. The comparisons between the built models and the precise scattered fields computed by a well-validated full-wave numerical method are investigated,and the results showgood agreements between each other.In order to deal with aliasing distortions of Doppler frequencies shown in time-frequency representation（ TFR） with aspect undersampling,an approach using adaptive segmental compressive sampling according to the aspect dependencies of the scattering centers is proposed. The random noise problem induced by compressive sampling is solved by employing a series of signal processing techniques of filtering,image transformation and Hough Transform. Three examples are presented to verify the effectiveness of this approach. The comparisons between the built models and the precise scattered fields computed by a well-validated full-wave numerical method are investigated,and the results showgood agreements between each other.

关 键 词：scattering center UNDERSAMPLING compressive sensing time-frequency representation parameter estimation 

分 类 号：TN958[电子电信—信号与信息处理]