Forward scattering micro radar is used for situation awareness; its operational range is relatively short because of the battery power and local horizon, the free space propagation model is not appropriate. The ground...Forward scattering micro radar is used for situation awareness; its operational range is relatively short because of the battery power and local horizon, the free space propagation model is not appropriate. The ground moving targets, such as humans, cars and tanks, have only comparable size with the transmitted signal wavelength; the point target model and the linear change of observation angle are not applicable. In this paper, the signal model of ground moving target is developed based on the case of forward scattering micro radar, considering the two-ray propagation model and area target model, and nonlinear change of observation angle as well as high order phase error. Furthermore, the analytical form of the received power from moving target has been obtained. Using the simulated forward scattering radar cross section, the received power of theoretical calculation is near to that of measured data. In addition, the simulated signal model of ground moving target is perfectly matched with the experimented data. All these results show the correctness of analytical calculation completely.展开更多
Independent component analysis (ICA) is a newly developed promising technique in signal processing applications. The effective separation and discrimination of functional Magnetic Resonance Imaging (fMRI) signals is a...Independent component analysis (ICA) is a newly developed promising technique in signal processing applications. The effective separation and discrimination of functional Magnetic Resonance Imaging (fMRI) signals is an area of active research and widespread interest. Therefore, the development of an ICA based fMRI data processing method is of obvious value both theoretically and in potential applications. In this paper, analyzed firstly is the drawback of the extant popular ICA-fMRI method where the adopted signal model assumes the independence of spatial distributions of the signals and noise. Then presented is a new fMRI signal model, which assumes the independence of temporal courses of signal and noise in a tiny spatial domain. Consequently we get a novel fMRI data processing method: Neighborhood independent component correlation algorithm. The effectiveness is elucidated through theoretical analysis and simulation tests, and finally a real fMRI data test is presented.展开更多
基金the Electro-Magnetic Remote Sensing Defence Technology Centre (EMRS DTC)established by the UK Ministry of Defence (Grant No. 1-27)+1 种基金the Program for New Century Excellent Talents in University (Grant No. NCET-06-0162)the National Natural Science Foundation of China (Grant Nos. 60890071-17, 60890072-13, 60890073)
文摘Forward scattering micro radar is used for situation awareness; its operational range is relatively short because of the battery power and local horizon, the free space propagation model is not appropriate. The ground moving targets, such as humans, cars and tanks, have only comparable size with the transmitted signal wavelength; the point target model and the linear change of observation angle are not applicable. In this paper, the signal model of ground moving target is developed based on the case of forward scattering micro radar, considering the two-ray propagation model and area target model, and nonlinear change of observation angle as well as high order phase error. Furthermore, the analytical form of the received power from moving target has been obtained. Using the simulated forward scattering radar cross section, the received power of theoretical calculation is near to that of measured data. In addition, the simulated signal model of ground moving target is perfectly matched with the experimented data. All these results show the correctness of analytical calculation completely.
基金This work was supported by the National Natural Science Foundation of China (Grant Nos. 39980009,69790080) the 973 Project (Grant No. G1998030503) the Foundation for University Key Teacher by the Ministry of Education, China Sichuan Youth Researche
文摘Independent component analysis (ICA) is a newly developed promising technique in signal processing applications. The effective separation and discrimination of functional Magnetic Resonance Imaging (fMRI) signals is an area of active research and widespread interest. Therefore, the development of an ICA based fMRI data processing method is of obvious value both theoretically and in potential applications. In this paper, analyzed firstly is the drawback of the extant popular ICA-fMRI method where the adopted signal model assumes the independence of spatial distributions of the signals and noise. Then presented is a new fMRI signal model, which assumes the independence of temporal courses of signal and noise in a tiny spatial domain. Consequently we get a novel fMRI data processing method: Neighborhood independent component correlation algorithm. The effectiveness is elucidated through theoretical analysis and simulation tests, and finally a real fMRI data test is presented.
