Efficient and Accurate Synthesis for Array Pattern Shaping.

Array pattern synthesis (APS) aims to create the desired array pattern as closely as possible to the prescribed mask template by varying the element excitations of the array. Herein, an efficient approach for the APS to control the sidelobe level is proposed. After designing the mask template to meet the prescribed sidelobe requirements and the waveform pattern, a set of element excitations is calculated through the Fourier transform performed on the projection the waveform pattern onto the mask template. Then, a desired array pattern can be synthesized from this updated set of excitation coefficients. The proposed APS approach directly presents a mathematical formulation of the exact set of excitations without any iterative optimization process. The proposed method is particularly suited for many array elements in linear antenna array. Thus, the proposed APS achieves substantial improvements in terms of computation complexity, performance, and ease of implementation in the algorithm when compared with conventional methods. Several simulation results are provided to verify the efficacy and effectiveness of the proposed method.

SAR Image Change Detection via Multiple-Window Processing with Structural Similarity.

In this paper, a synthetic aperture radar (SAR) change detection approach is proposed based on a structural similarity index measure (SSIM) and multiple-window processing (MWP). The proposed scheme is performed in two steps: (1) generation of a coherence image based on MWP associated with SSIM and (2) gamma correction (GC) filtering. The proposed method is capable of providing a high-quality coherence image because the MWP operation based on SSIM has high sensitivity to the similarity measure for intensity between two SAR images. By finding an optimum value of order of GC, the proposed method can considerably reduce the effect of speckle noise on the coherence image, while retaining nearly all the information related to changed region involved in the change detection map. Several experimental results are presented to demonstrate the effectiveness of the proposed scheme.

In-situ nanospectroscopic pH monitoring by plasmon resonance energy transfer (PRET).

Real-time detection of pH value in a living cell is in central importance for research about cells and diseases. In spite of the great advances in science and technology, pH measurement in a living cell is still limited in spatial resolution, in-situ detection, and intracellular monitoring. Here, we designed a nanoscale pH meter by Plasmon Resonance Energy Transfer (PRET). In order to highly sensitively measure pH with nanoscale spatial resolution, we choose 80 nm spherical gold nanoparticle (GNP) and phenol red which is commonly used in cell media for pH determination. The resonance energy of GNP is transferred to phenol red because the scattering intensity of GNP is overlapped with the second absorption intensity of phenol red at near 560 nm. Meanwhile, the absorption intensity of phenol red molecules is changing with pH value of the solution. For that reason, the intensity of PRET from GNP to phenol red molecules also changes by the acidity of phenol red solution. Then we can detect pH values with nanoscale spatial resolution through the Rayleigh scattering intensity of GNP. As we changed pH value from 6.0 to 9.0, the scattering intensity of GNP is decreased because the absorbance of phenol red at 560 nm wavelength is increased with increasing pH value. The Gaussian peak of a difference in Rayleigh scattering spectra of GNP between pH 6.0 and pH 9.0 indicates exactly the same as UV-vis spectral difference between basic and acidic phenol red solution. We expect that this pH measuring technique has a significant impact on the pH detection of living cells with nanoscale, and it can make possibility to image the cell structure by pH variation.