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81.
基于FFT的快速SAR分布目标回波模拟算法 总被引:10,自引:0,他引:10
大面积分布目标的合成孔径雷达 (SAR)回波模拟需要大量的运算 ,文中提出了一种合成孔径雷达回波模拟的快速算法 ,算法利用时域插值和FFT来缩减运算量 ,对于大面积目标回波模拟时 ,该算法有很高的效率。文中详细分析sinc函数插值所带来的误差以及补偿方法 ,并在次基础上提出了一种利用增采样插值方法 ,该方法以增加少量运算为代价 ,使得模拟精度的大幅度提高。文中比较了传统方法和基于FFT的快速SAR分布目标回波模拟算法的模拟结果 ,证明了这种快速算法确实行之有效 相似文献
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84.
将传统上广泛使用的“种子法”和“矢量求交法”的思想相结合 ,提出了一种基于约束Delaunay三角网结构的多边形生成算法。详细描述了该方法的基本思想 ,在实验基础上分析了算法的特点。 相似文献
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一种组合优化的多边形化简方法 总被引:2,自引:0,他引:2
以多边形轮廓为目标 ,依据曲线特征点将其分解为一系列的弯曲特征 ,并对此弯曲特征集实施组合优化 ,将入围弯曲首尾相连 ,即可得到最终的化简结果 相似文献
87.
According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for CaseⅠand CaseⅡwater bodies respectively. The monthly chlorophyll distribution in the East China Sea in 1998 was obtained from this improved model on calculation results of SeaBAM. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distributions in the East China Sea in 1998 were obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays the lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m2/d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m2/a. The research on the seasonal variety mechanism of primary productivity shows that several factors that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River diluted water variety, the euphotic depth, ocean current variety, etc. But the main influencing factors may be different in each local sea area. 相似文献
88.
采用Atkinson方法,基于遗传算法,利用呼和浩特数字地震台网7个子台记录的9次质量较高的地震事件资料,计算了内蒙古中西部地区的品质因子Q值和非弹性衰减系数c(f)。在所研究的频率范围内,前者和频率.厂有很好的线形关系:Q(f)=116.8f^1.000后者与频率.厂的变化关系不明显。在此基础上采用Moya方法反演了7个地震台的场地响应和地震的震源参数,并对它们之间的相互关系进行了讨论。结果显示在所研究的频率域内7个基岩台站的场地均不同程度的存在放大作用,其次震源参数间具有较好的线性关系。本文还详细介绍了Atkinson方法和Moya方法的原理和计算步骤。 相似文献
89.
In our previous study (Earthquake Engineering and Structural Dynamics 2003; 32 :2301), we have developed a probabilistic algorithm for active control of structures. In the probabilistic control algorithm, the control force is determined by the probability that the structural energy exceeds a specified target critical energy, and the direction of a control force is determined by the Lyapunov controller design method. In this paper, an experimental verification of the proposed probabilistic control algorithm is presented. A three‐story test structure equipped with an active mass driver (AMD) has been used. The effectiveness of the control algorithm has been examined by exciting the test structure using a sinusoidal signal, a scaled El Centro earthquake and a broadband Gaussian white noise; and, especially, experiments on control have been performed under different conditions to that of system identification in order to prove the stability and robustness of the proposed control algorithm. The experimental results indicate that the probabilistic control algorithm can achieve a significant response reduction under various types of ground excitations even when the modeling error exists. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
90.
Xavier Emery 《Stochastic Environmental Research and Risk Assessment (SERRA)》2005,19(5):348-360
This work deals with the geostatistical simulation of a family of stationary random field models with bivariate isofactorial
distributions. Such models are defined as the sum of independent random fields with mosaic-type bivariate distributions and
infinitely divisible univariate distributions. For practical applications, dead leaf tessellations are used since they provide
a wide range of models and allow conditioning the realizations to a set of data via an iterative procedure (simulated annealing).
The model parameters can be determined by comparing the data variogram and madogram, and enable to control the spatial connectivity
of the extreme values in the realizations. An illustration to a forest dataset is presented, for which a negative binomial
model is used to characterize the distribution of coniferous trees over a wooded area. 相似文献