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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Regularized Deconvolution Method for the Resolution Enhancement of a Dual-Frequency Polarized Scatterometer on WCOM
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Regularized Deconvolution Method for the Resolution Enhancement of a Dual-Frequency Polarized Scatterometer on WCOM

机译:WCOM上双频极化散射仪分辨率提高的正则反褶积方法

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摘要

A dual-frequency polarized scatterometer (DPSCAT) is proposed for the Chinese Water Cycle Observation Mission (WCOM) to be launched around 2020. DPSCAT is used to measure the snow water equivalent (SWE) and the freeze/thaw state, which requires a measurement precision of 0.5 dB and a relatively higher spatial resolution (2–5 km) than the regular scatterometers (about 25 km). Therefore, the conventional range-gate dechirping along with the Doppler beam sharpening (DBS) technique is used by DPSCAT to achieve high range and azimuth resolution simultaneously. However, DBS cannot improve the azimuth resolution over the nadir swath; thus, a new data processing, namely regularized deconvolution method (RDM), is explored to address this problem. In this paper, a quantitative analysis model is developed for RDM in order to study two crucial issues, i.e., the spatial resolution (mainly for the nadir swath) and the accuracy/precision of the backscatter measurements after resolution enhancement. Normally, the measurement precision and spatial resolution cannot be improved simultaneously using RDM. The accuracy/precision degrades as the spatial resolution improves, and vice versa. Moreover, they both degrade as the measurement noise or uncertainty increases, which latter is usually defined as the normalized standard deviation of the measurements ( Kp). In case of SWE retrieval that requires a reconstructed measurement precision of 0.5 dB, the best spatial resolution resolved by RDM is 3 km for Kp = 7%, 4 km for Kp = 10%, and 5 km for Kp = 12%.
机译:拟在2020年左右启动的中国水循环观测任务(WCOM)中使用双频极化散射仪(DPSCAT)。DPSCAT用于测量雪水当量(SWE)和冻结/融化状态,需要进行测量精度为0.5 dB,并且比常规散射仪(约25 km)具有更高的空间分辨率(2–5 km)。因此,DPSCAT使用常规的距离门去抖和多普勒波束锐化(DBS)技术来同时实现高距离和方位分辨率。但是,星展银行无法提高天底幅的方位角分辨率。因此,探索了一种新的数据处理方法,即正则化反卷积方法(RDM),以解决该问题。在本文中,为RDM开发了定量分析模型,以研究两个关键问题,即空间分辨率(主要针对天底幅)和分辨率增强后反向散射测量的精度/精度。通常,使用RDM无法同时提高测量精度和空间分辨率。精度/精度会随着空间分辨率的提高而降低,反之亦然。此外,它们都随着测量噪声或不确定性的增加而降低,后者通常被定义为测量的标准化标准偏差(Kp)。在SWE检索需要重建的测量精度为0.5 dB的情况下,RDM解析的最佳空间分辨率对于Kp = 7%为3 km,对于Kp = 10%为4 km,对于Kp = 12%为5 km。

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