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Microwave tomographic inversion technique based on stochastic approach for rainfall fields monitoring

机译:基于随机方法的微波层析成像反演技术用于降雨场监测

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The microwave tomographic inversion technique (MTIT) proposed in 1991 for reconstruction of rainfall fields at ground through microwave attenuation measurements is reconsidered. A new algorithm for data inversion is presented [referred to as stochastic reconstruction technique (SRT)] that generally performs better than the one originally adopted [referred to as arithmetic reconstruction technique (ART)]. Improvement is achieved in spatial definition and general reliability of rainfall field reconstruction. The new model adopted to represent the reconstructed rainfall fields leads to a completely different strategy for the inversion problem, and this strategy is based on a global optimization stochastic technique (GOST). Results obtained through the SRT-MTIT are presented in the paper and compared to those obtained by employing the ART-MTIT. It also is shown that, based on the SRT-MTIT approach, fast and reliable time tracking of rainfall events is made possible by exploiting previous reconstructions and by the improved long-term physical consistency of the model adopted for rainfall field decomposition.
机译:重新考虑了1991年提出的微波层析成像反演技术(MTIT),该技术通过微波衰减测量来重建地面的降雨场。提出了一种新的数据反转算法[称为随机重建技术(SRT)],该算法通常比最初采用的算法[称为算术重建技术(ART)]更好。降雨场重建的空间清晰度和总体可靠性得到改善。用来表示重建降雨场的新模型导致了针对反演问题的完全不同的策略,并且该策略基于全局优化随机技术(GOST)。本文介绍了通过SRT-MTIT获得的结果,并与采用ART-MTIT获得的结果进行了比较。还表明,基于SRT-MTIT方法,通过利用先前的重建方法以及通过用于降雨场分解的模型的改进的长期物理一致性,可以对降雨事件进行快速可靠的时间跟踪。

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