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A. Ian McLeod K. W. Hipel 《Stochastic Environmental Research and Risk Assessment (SERRA)》1995,9(3):171-205
Current methods of estimation of the univariate spectral density are reviewed and some improvements are made. It is suggested that spectral analysis may perhaps be best thought of as another exploratory data analysis (EDA) tool which complements, rather than competes with, the popular ARMA model building approach. A new diagnostic check for ARMA model adequacy based on the nonparametric spectral density is introduced. Additionally, two new algorithms for fast computation of the autoregressive spectral density function are presented. For improving interpretation of results, a new style of plotting the spectral density function is suggested. Exploratory spectral analyses of a number of hydrological time series are performed and some interesting periodicities are suggested for further investigation. The application of spectral analysis to determine the possible existence of long memory in natural time series is discussed with respect to long riverflow, treering and mud varve series. Moreover, a comparison of the estimated spectral densities suggests the ARMA models fitted previously to these datasets adequately describe the low frequency component. Finally, the software and data used in this paper are available by anonymous ftp from fisher.stats.uwo.ca. 相似文献
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Li Chao 《Mathematical Geology》1998,30(1):43-56
A multidimensional version of the time varying periodogram has been developed. The estimation method based on the multidimensional time-varying periodogram has been applied to a nonstationary multidimensional storm model. This work proposes that the multidimensional time varying periodogram is capable of estimating nonstationary spectral density functions in space and time. 相似文献
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利用GNSS-MR(Global Navigation Satellite System Multipath Reflectometry)技术反演积雪深度是近年来一种新兴的卫星遥感技术。目前大多数研究仅使用GPS(Global Position System)数据限制了该技术的发展,为了扩展GNSS-MR算法的应用,介绍了基于GNSS-MR算法的雪深反演模型。首先,通过多项式拟合分解GLONASS观测数据获取高精度的信噪比残差序列;然后,利用Lomb-Scargle谱分析法对其进行频谱分析可解算雪深值。选取IGS中心的YEL2站2015年11月到2016年6月共243天的GLONASS卫星L1波段反射信号的SNR数据进行实例分析,并以美国国家气象数据中心提供的加拿大Y-H (Yellowknife Henderson)气象站的实测雪深数据为真值,将反演雪深与实测雪深进行对比验证。所得实验结果如下:(1)与GPS卫星的反演值相比,基于GLONASS-MR(GLONASS Multipath Reflectometry)技术反演积雪深度的精度同样能达到厘米级,RMSE仅3.3 cm,反演值与实测值的空间分布趋势一致且相关性较强,其相关系数R2高达0.969;(2)不同的积雪深度对信噪比的振幅频率与垂直反射距离具有直接影响;(3)对同一卫星而言,信噪比的频谱振幅强度峰值与其对应的反演值存在线性相关;(4)在相同条件下,采用多颗GLONASS卫星数据比单颗GLONASS卫星数据反演雪深的效果明显更优。基于反演的高时间分辨率产品,分析该地区雪深日变化的情况,实验结果表明基于陆基CORS站的GLONASS-MR技术在用于实时、连续的雪深变化监测方面具有良好的潜力和可行性。 相似文献
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针对现有GPS海浪测量技术的不足,提出基于TRACK的GPS海浪测量方法,即利用TRACK解得海上载体高精度的垂向位移,经浪潮分离提取海浪信号,采用周期图法估计海浪信号的功率谱,计算海浪要素。利用实测数据进行实验,结果表明,平均波高和平均周期与测波仪结果差异分别小于2 cm和0.25 s,验证了本文方法的有效性。 相似文献
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基于GPS新型L5信号的地表雪深反演研究 总被引：1，自引：0，他引：1
利用GPS多路径反射信号测量地表雪深具有全天候和高时空分辨率的特点,因此其可作为一种代替气象站监测雪深的新手段。然而,先前大多数研究仅使用了GPS L1和L2C波段信噪比数据探测积雪深度。为验证新型的L5信号在雪深反演方面的优越性,本文阐述了GPS-R技术反演雪深的原理,利用Lomb-Scargle周期图法所处理的受积雪表层影响的信噪比数据计算了频谱振幅强度,通过获取频谱特征值与天线高度的关系求解雪深值,最后分别与L1反演结果和实测雪深数据进行了对比。试验结果表明：与现有的GPS-R测量雪深结果相比,利用新型的L5反射信号反演地表雪深的精度更佳;采用GPS-R技术探测雪深对把握测站区域内的雪深变化情况和淡水资源储量具有重要价值。 相似文献
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对东川蒋家沟发生的一次阵性泥石流序列进行周期性分析。然后根据分析结果，提出了泥石流发生相关的几个问题。 相似文献
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Li Wei L&#;Daren Shoichiro Fukao Mamoru Yamamoto Toshitaka Tsu Susumu Kato 《Acta Meteorologica Sinica》1991,5(3):293-298
Preliminary results of the wind velocity estimation using the Maximum Entropy Method (MEM) to MUradar observation data sets are presented. The comparison of the results from the periodogram method and theMEM shows that the MEM estimation is reliable, and has higher accuracy, resolution and detectability than theestimation from periodogram method. The high accuracy power spectrum obtained by the MEM is veryuseful to studying the atmospheric turbulence structure. However. the MEM needs the longer computingtime for obtaining the high accuracy spectrum. Particularly, the estimation of MEM will bring serious devia-tion at lower signal-to-noise ratio. 相似文献
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Based on the maximum-entropy(ME)principle,a new power spectral estimator for random waves is derived in the form of S～(ω)=a/8H~2(2π)~(d 1)ω~-~((d 2))exp[-b(2π/ω)~n],by solving a variational problem subject to some quite general constraints.This robust method is comprehensive enough to describe the wave spectra even in extreme wave conditions and is superior to periodogram method that is not suitable to process comparatively short or intensively unsteady signals for its tremendous boundary effect and some inherent defects of FFT.Fortunately,the newly derived method for spectral estimation works fairly well,even though the sample data sets are very short and unsteady,and the reliability and efficiency of this spectral estimator have been preliminarily proved. 相似文献