Estimation precision of Displaced Phase Center Algorithm(DPCA) is affected by the number of displaced phase center pairs,the bandwidth of transmitting signal and many other factors.Detailed analysis is made on DPCA...Estimation precision of Displaced Phase Center Algorithm(DPCA) is affected by the number of displaced phase center pairs,the bandwidth of transmitting signal and many other factors.Detailed analysis is made on DPCA's estimation precision.Analysis results show that the directional vector estimation precision of DPCA is low,which will produce accumulating errors when phase cen-ters' track is estimated.Because of this reason,DPCA suffers from accumulating errors seriously.To overcome this problem,a method combining DPCA with Sub Aperture Image Correlation(SAIC) is presented.Large synthetic aperture is divided into sub-apertures.Micro errors in sub-aperture are estimated by DPCA and compensated to raw echo data.Bulk errors between sub-apertures are esti-mated by SAIC and compensated directly to sub-aperture images.After that,sub-aperture images are directly used to generate ultimate SAS image.The method is applied to the lake-trial dataset of a 20 kHz SAS prototype system.Results show the method can successfully remove the accumulating error and produce a better SAS image.展开更多
基金Supported by the National High Technology Research and Development Program of China (863 Program, 2007AA 091101)
文摘Estimation precision of Displaced Phase Center Algorithm(DPCA) is affected by the number of displaced phase center pairs,the bandwidth of transmitting signal and many other factors.Detailed analysis is made on DPCA's estimation precision.Analysis results show that the directional vector estimation precision of DPCA is low,which will produce accumulating errors when phase cen-ters' track is estimated.Because of this reason,DPCA suffers from accumulating errors seriously.To overcome this problem,a method combining DPCA with Sub Aperture Image Correlation(SAIC) is presented.Large synthetic aperture is divided into sub-apertures.Micro errors in sub-aperture are estimated by DPCA and compensated to raw echo data.Bulk errors between sub-apertures are esti-mated by SAIC and compensated directly to sub-aperture images.After that,sub-aperture images are directly used to generate ultimate SAS image.The method is applied to the lake-trial dataset of a 20 kHz SAS prototype system.Results show the method can successfully remove the accumulating error and produce a better SAS image.
