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231.
Coastal marine gravity modeling faces challenges due to the degradation of the quality and poor coverage of altimeter data in coastal regions. The effective fusion of shipborne gravity data and altimeter-derived marine gravity data can make shipborne gravity data more useful for the accurate estimation of altimeter-derived coastal marine gravity. A mean sea surface height constraint factor (MSSHCF) method based on the ordinary kriging method and the remove-restore technique is proposed to fuse altimeter-derived gravity model with shipborne gravity data. In this method, all data are standardized during the interpolation process to reduce the error and mean sea surface as a vertical variable is added to the semi-variance function in ordinary kriging to obtain the residual shipborne gravity as corrected data source. The coastal marine gravity models V2.1 and V3.1 which fused altimeter-derived gravity data with shipborne gravity data and V1.1 without shipborne gravity data at a spatial resolution of 1′×1′ can be obtained. Validation experiments show that the accuracy of the gravity model V3.1 obtained by the MSSHCF method more closely agrees with the validated gravity model DTU17 and SS V31 than the model V2.1 obtained by the ordinary kriging interpolation method and the V1.1 model. Our results were validated against shipborne gravity data; the accuracy of model V3.1 was 4.95 % higher than the model V1.1 in South China Sea area A and 2.48 % higher in South China Sea area B. Meanwhile, the accuracy of model V3.1 was 2.07 % higher than model V2.1 in South China Sea area A and 2.42 % higher in South China Sea area B. The effects of distance from the coast and sea depth on the marine gravity model were also evaluated. The results show that the gravity model V3.1 has higher accuracy with the change in ocean distance and depth than the V2.1 and V1.1 gravity models. Thus, our study shows that the MSSHCF method effectively refines coastal altimeter-derived gravity using shipborne gravity data.  相似文献   
232.
In radiation detector signal processing, usually, the charge-sensitive preamplifier converts the small charge signal coming from the semiconductor-based detector into voltage form and then the signal is further amplified to measure the energy of the incoming radiation. The voltage pulse from a charge-sensitive preamplifier (CSPA) is amplified using a shaping amplifier which reduces the signal bandwidth. To achieve better energy resolution, precise measurement of the peak amplitude of shaping amplifier output is required. The signal processing methods are available in which the signal from the charge-sensitive preamplifier can be directly digitized using high-speed Analog to Digital Converters (ADC), and then further signal processing such as gain and shaping is carried out inside the Field Programmable Gate Arrays (FPGA). For multiple detector systems, digital signal processing methods are quite difficult to implement in Field Programmable Gate Arrays (FPGA). In this context, The development of an alternative technique is initiated that uses a charge-sensitive preamplifier, shaping amplifier, low sampling analog-to-digital converter, and FPGA, where LaGrange’s interpolation technique is implemented in FPGA to precisely measure the peak of the analog pulse. In this paper, the comparison of the proposed method with other pulse amplitude measurement techniques is discussed. Results show that the implemented technique gives similar energy resolution compared to digital pulse processing and standard peak detector-based techniques.  相似文献   
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