Compared to the rank reduction estimator （RARE） based on second-order statistics （called SOS-RARE）, the RARE employing fourth-order cumulants （referred to as FOC-RARE） is capable of dealing with more sources and...Compared to the rank reduction estimator （RARE） based on second-order statistics （called SOS-RARE）, the RARE employing fourth-order cumulants （referred to as FOC-RARE） is capable of dealing with more sources and mitigating the negative influences of the Gaussian colored noise. However, in the presence of unexpected modeling errors, the resolution behavior of the FOC-RARE also deteriorate significantly as SOS-RARE, even for a known array covariance matrix. For this reason, the angle resolution capability of the FOC-RARE was theoretically analyzed. Firstly, the explicit formula for the mathematical expectation of the FOC-RARE spatial spectrum was derived through the second-order perturbation analysis method. Then, with the assumption that the unexpected modeling errors were drawn from complex circular Gaussian distribution, the theoretical formulas for the angle resolution probability of the FOC-RARE were presented. Numerical experiments validate our analytical results and demonstrate that the FOC-RARE has higher robustness to the unexpected modeling en＇ors than that of the SOS-RARE from the resolution point of view.展开更多
Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its ...Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its radar image is evaluated by the average mutual information measure. A conditional (transition) probability density function (PDF) of the SAR imaging system is derived by analyzing the system and a closed form of the information content is found. It is shown that the information content obtained by the SAR imaging system from an independent sample of echoes will decrease and the total information content obtained by the SAR imaging system will increase with an increase in the number of looks. Because the total average mutual information is also used to define a measure of radiometric resolution for radar images, it is shown that the radiometric resolution of a radar image of terrain will be improved by spatial averaging. In addition, the imaging process and the data compression process for SAR are each treated as an independent generalized communication channel. The effects of data compression upon radiometric resolution for SAR are studied and some conclusions are obtained.展开更多
基金Project(61201381)supported by the National Nature Science Foundation of ChinaProject(YP12JJ202057)supported by the Future Development Foundation of Zhengzhou Information Science and Technology College,China
文摘Compared to the rank reduction estimator （RARE） based on second-order statistics （called SOS-RARE）, the RARE employing fourth-order cumulants （referred to as FOC-RARE） is capable of dealing with more sources and mitigating the negative influences of the Gaussian colored noise. However, in the presence of unexpected modeling errors, the resolution behavior of the FOC-RARE also deteriorate significantly as SOS-RARE, even for a known array covariance matrix. For this reason, the angle resolution capability of the FOC-RARE was theoretically analyzed. Firstly, the explicit formula for the mathematical expectation of the FOC-RARE spatial spectrum was derived through the second-order perturbation analysis method. Then, with the assumption that the unexpected modeling errors were drawn from complex circular Gaussian distribution, the theoretical formulas for the angle resolution probability of the FOC-RARE were presented. Numerical experiments validate our analytical results and demonstrate that the FOC-RARE has higher robustness to the unexpected modeling en＇ors than that of the SOS-RARE from the resolution point of view.
文摘Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its radar image is evaluated by the average mutual information measure. A conditional (transition) probability density function (PDF) of the SAR imaging system is derived by analyzing the system and a closed form of the information content is found. It is shown that the information content obtained by the SAR imaging system from an independent sample of echoes will decrease and the total information content obtained by the SAR imaging system will increase with an increase in the number of looks. Because the total average mutual information is also used to define a measure of radiometric resolution for radar images, it is shown that the radiometric resolution of a radar image of terrain will be improved by spatial averaging. In addition, the imaging process and the data compression process for SAR are each treated as an independent generalized communication channel. The effects of data compression upon radiometric resolution for SAR are studied and some conclusions are obtained.
