Three kinds of coplanar waveguides （CPWs） are designed and fabricated on different silicon substrates---common low-resistivity silicon substrate （LRS）, LRS with a 3μm-thick silicon oxide interlayer, and high-resi...Three kinds of coplanar waveguides （CPWs） are designed and fabricated on different silicon substrates---common low-resistivity silicon substrate （LRS）, LRS with a 3μm-thick silicon oxide interlayer, and high-resistivity silicon （HRS） substrate. The results show that the microwave loss of a CPW on LRS is too high to be used, but it can be greatly reduced by adding a thick interlayer of silicon oxide between the CPW transmission lines and the LRS.A CPW directly on HRS shows a loss lower than 2dB/cm in the range of 0-26GHz and the process is simple,so HRS is a more suitable CPW substrate.展开更多
The resolution of seismic data is critical to seismic data processing and the subsequent interpretation of fine structures. In conventional resolution improvement methods, the seismic data is assumed stationary and th...The resolution of seismic data is critical to seismic data processing and the subsequent interpretation of fine structures. In conventional resolution improvement methods, the seismic data is assumed stationary and the noise level not changes with space, whereas the actual situation does not satisfy this assumption, so that results after resolution improvement processing is not up to the expected effect. To solve these problems, we propose a seismic resolution improvement method based on the secondary time-frequency spectrum. First, we propose the secondary time-frequency spectrum based on S transform （ST） and discuss the reflection coefficient sequence and time-dependent wavelet in the secondary time frequency spectrum. Second, using the secondary time frequency spectrum, we design a two- dimensional filter to extract the amplitude spectrum of the time-dependent wavelet. Then, we discuss the improvement of the resolution operator in noisy environments and propose a novel approach for determining the broad frequency range of the resolution operator in the time- fi＇equency-space domain. Finally, we apply the proposed method to synthetic and real data and compare the results of the traditional spectrum-modeling deconvolution and Q compensation method. The results suggest that the proposed method does not need to estimate the Q value and the resolution is not limited by the bandwidth of the source. Thus, the resolution of the seismic data is improved sufficiently based on the signal-to-noise ratio （SNR）.展开更多
文摘Three kinds of coplanar waveguides （CPWs） are designed and fabricated on different silicon substrates---common low-resistivity silicon substrate （LRS）, LRS with a 3μm-thick silicon oxide interlayer, and high-resistivity silicon （HRS） substrate. The results show that the microwave loss of a CPW on LRS is too high to be used, but it can be greatly reduced by adding a thick interlayer of silicon oxide between the CPW transmission lines and the LRS.A CPW directly on HRS shows a loss lower than 2dB/cm in the range of 0-26GHz and the process is simple,so HRS is a more suitable CPW substrate.
基金financially supported by the National 973 Project(No.2014CB239006)the National Natural Science Foundation of China(No.41104069 and 41274124)the Fundamental Research Funds for Central Universities(No.R1401005A)
文摘The resolution of seismic data is critical to seismic data processing and the subsequent interpretation of fine structures. In conventional resolution improvement methods, the seismic data is assumed stationary and the noise level not changes with space, whereas the actual situation does not satisfy this assumption, so that results after resolution improvement processing is not up to the expected effect. To solve these problems, we propose a seismic resolution improvement method based on the secondary time-frequency spectrum. First, we propose the secondary time-frequency spectrum based on S transform （ST） and discuss the reflection coefficient sequence and time-dependent wavelet in the secondary time frequency spectrum. Second, using the secondary time frequency spectrum, we design a two- dimensional filter to extract the amplitude spectrum of the time-dependent wavelet. Then, we discuss the improvement of the resolution operator in noisy environments and propose a novel approach for determining the broad frequency range of the resolution operator in the time- fi＇equency-space domain. Finally, we apply the proposed method to synthetic and real data and compare the results of the traditional spectrum-modeling deconvolution and Q compensation method. The results suggest that the proposed method does not need to estimate the Q value and the resolution is not limited by the bandwidth of the source. Thus, the resolution of the seismic data is improved sufficiently based on the signal-to-noise ratio （SNR）.
