In this paper, a novel synthetic aperture radar (SAR) imaging method based on L 1/2 regularization is proposed. Our method implements SAR imaging from compressed measurements with high resolution, enhanced features, ...
详细信息
In this paper, a novel synthetic aperture radar (SAR) imaging method based on L 1/2 regularization is proposed. Our method implements SAR imaging from compressed measurements with high resolution, enhanced features, reduced sidelobes and suppressed artifacts. Real SAR data experiments are implemented to demonstrate the outperformance of our method. The experiment results demonstrate that our method needs far below the traditional Nyquist rate to guarantee successful imaging. Compared to the prevalent L 1 regularization-based methods, there is a significant reduction of the sampling rate for SAR imaging. The sampling rate used by our method is about half of the L 1 regularization-based methods in the real SAR data experiments.
We model the sum and product riddle in public announcement logic, which is interpreted on an epistemic Kripke model. The model is symbolically represented as a finite state program with n agents. A model checking meth...
详细信息
We model the sum and product riddle in public announcement logic, which is interpreted on an epistemic Kripke model. The model is symbolically represented as a finite state program with n agents. A model checking method to the riddle is developed by using the BDD-based symbolic model checking algorithm for logic of knowledge we developed in [7]. The method is implemented by extending the model checker MCTK [7] and then the solution of the riddle is verified successfully.
暂无评论