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基于严密波束归位模型的多波束测深点不确定度改进方法 总被引：1，自引：0，他引：1
利用不确定度可有效对多波束测深成果质量进行评估,针对现有不确定度计算模型因近似或简化导致一定误差的问题,本文提出一种基于严密波束归位模型的多波束测深点不确定度改进方法。首先分析了多波束测深过程中的各项误差源,基于误差传播定律与严密波束归位模型,详细推导了各误差源在波束归位各阶段的误差传播情况,最终得出了多波束测深成果不确定度的计算模型。文中利用实测数据计算了每个测深点的不确定度,绘制了单Ping扇面及条带的不确定度分布图,有利于直观、全面地了解所有测深点的误差变化趋势;计算结果与常用HGM不确定度模型进行了对比,表明本文方法更具合理性,对多波束测深成果的质量评估具有一定的参考价值。 相似文献
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为全面准确地评定GNSS(Global Navigation Satellite System)海洋浮标测得瞬时海面高程的动态不确定度,根据GNSS海洋浮标的工作原理、系统组成及数据处理方法,提出了针对具体测量过程的瞬时海面高程动态不确定度评定方法。将浮标动态测量过程分解为静态测量过程的集合,采用GUM(Guide to the Expression of Uncertainty in Measurement)方法建立了测量模型,详细分析和计算了静态测量过程中瞬时海面高程的不确定度分量:GNSS高程不确定度、GNSS天线高程改正不确定度和高程异常不确定度,最后合成瞬时海面高程的动态标准不确定度和动态扩展不确定度。使用该方法对近海GNSS浮标测量结果进行了动态不确定度评定,验证了此方法的可行性,也为评价GNSS浮标测量结果质量提供了有效依据。 相似文献
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文中分析了实验室盐度计校准不确定度来源项,按不确定度的评定方法,以实例形式分析评定了校准结果的不确定度。 相似文献
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文章分析了CTD温度实验室校准不确定度来源项,按不确定度的评定方法,以实例形式分析评定了CTD温度实验室校准结果的不确定度。 相似文献
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文中分析了CTD电导率实验室校准不确定度来源项,按不确定度的评定方法,以实例形式分析评定了CTD电导率实验室校准结果的不确定度。 相似文献
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电位测定法测海水氧化还原电位的不确定度评定 总被引：2，自引：0，他引：2
采用电位测定法对实际海水的氧化还原电位进行测定,分析了影响测量不确定度的主要来源,对曲线拟合、测定过程的标准溶液的使用、仪器使用和测量重复性等影响不确定度的分量进行分析,按JJF1059—1999《测量不确定度评定与表示》的规定进行合成,最终给出扩展不确定度。结果表明,实际海水电位值的合成标准不确定度为14.18 mV,扩展不确定度为28.4 mV(近似95%置信概率)。这样结果的表达更加客观和真实,更具有参考意义。 相似文献
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文章依据相关国家标准,结合海洋环境监测站的实际工作需求,针对环境自动观测系统的盐度传感器,提出新的现场校准方法,即直接比较法;根据不确定度来源,分别计算由测量重复性、盐度标准器、测量环境、测量人员和恒温水槽引入的不确定度分量并合成标准不确定度,据此计算扩展不确定度和合成标准不确定度的有效自由度,由此得出盐度传感器现场校准测量结果的不确定度为0.17。本研究提出的盐度传感器现场校准方法更契合海水盐度的变化规律,可实现盐度分量的量值溯源,具有准确度高和溯源途径清晰的特点;不确定度评定方法科学合理,且具有一定的推广价值。 相似文献
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CUBE算法及其在多波束数据处理中的应用 总被引：5，自引：0，他引：5
阐述了一种基于表面生成的多波束数据处理方法——CUBE(Combined Uncertainty and Bathymetry Estimator)算法,用该方法可以对观测区域网格节点"真实"水深及相关误差进行估计。与从测量水深中选择出"最佳"数据的手工交互方式的多波束数据编辑手段不同,CUBE算法具有很强的抗差性和较高的效率,适合于实时多波束数据处理。对南海某测区多波束数据处理结果表明,在没有人工干预的情况下,利用CUBE算法去噪生成的海底DTM图与手工编辑生成的相当吻合。CUBE算法和手工编辑方法综合对比得出,CUBE算法能够很好地保留水深地形细节,在计算效率、误差评估、实时处理等方面比手工编辑方法具有较大的优势。 相似文献
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为科学评价测量结果的可靠性，对海水中137Cs γ能谱分析方法的不确定度进行了评估。根据《化学分析中不确定度的评估指南》，分析不确定度的来源并逐一对各不确定度分量进行了量化，最终计算了合成相对标准不确定度。结果表明，影响海水中137Cs γ能谱测量不确定度的因素分别为样品源137Cs峰区计数、标准源活度、取样体积、化学回收率、本底137Cs峰区计数及标准源137Cs峰区计数，其中样品源137Cs峰区计数的不确定度贡献最为突出。对于137Cs活度浓度为1.28 mBq/L的海水样品，其合成相对标准不确定度为9.78%。 相似文献
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基于浮游植物吸收的海洋初级生产力模型的不确定性分析 总被引：1，自引：1，他引：0
Satellite-derived phytoplankton pigment absorption(a_(ph)) has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production(NPP). In this study, an a_(ph)-based NPP model(Ab PM) with four input parameters including the photosynthetically available radiation(PAR), diffuse attenuation at 490 nm(K_d(490)), euphotic zone depth(Z_(eu)) and the phytoplankton pigment absorption coefficient(a_(ph)) is compared with the chlorophyll-based model and carbon-based model. It is found that the Ab PM has significant advantages on the ocean NPP estimation compared with the chlorophyll-based model and carbonbased model. For example, Ab PM greatly outperformed the other two models at most monitoring sites and had the best accuracy, including the smallest values of RMSD and bias for the NPP estimate, and the best correlation between the observations and the modeled NPPs. In order to ensure the robustness of the model, the uncertainty in NPP estimates of the Ab PM was assessed using a Monte Carlo simulation. At first, the frequency histograms of simple difference(δ), and logarithmic difference(δ~(LOG)) between model estimates and in situ data confirm that the two input parameters(Z_(eu) and PAR) approximate the Normal Distribution, and another two input parameters(a_(ph) and K_d(490)) approximate the logarithmic Normal Distribution. Second, the uncertainty in NPP estimates in the Ab PM was assessed by using the Monte Carlo simulation. Here both the PB(percentage bias), defined as the ratio of ΔNPP to the retrieved NPP, and the CV(coefficient of variation), defined as the ratio of the standard deviation to the mean are used to indicate the uncertainty in the NPP brought by input parameter to Ab PM model. The uncertainty related to magnitude is denoted by PB and the uncertainty related to scatter range is denoted by CV.Our investigations demonstrate that PB of NPP uncertainty brought by all parameters with an annual mean of5.5% covered a range of –5%–15% for the global ocean. The PB uncertainty of Ab PM model was mainly caused by a_(ph); the PB of NPP uncertainty brought by a_(ph) had an annual mean of 4.1% for the global ocean. The CV brought by all the parameters with an annual mean of 105% covered a range of 98%–134% for global ocean. For the coastal zone of Antarctica with higher productivity, the PB and CV of NPP uncertainty brought by all parameters had annual means of 7.1% and 121%, respectively, which are significantly larger than those obtained in the global ocean. This study suggests that the NPPs estimated by Ab PM model are more accurate than others, but the magnitude and scatter range of NPP errors brought by input parameter to Ab PM model could not be neglected,especially in the coastal area with high productivity. So the improving accuracy of satellite retrieval of input parameters should be necessary. The investigation also confirmed that the SST related correction is effective for improving the model accuracy in low temperature condition. 相似文献
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Multibeam echosounders (MBES) have become a widely used acoustic remote sensing tool to map and study the seafloor, providing co-located bathymetry and seafloor backscatter. Although the uncertainty associated with MBES-derived bathymetric data has been studied extensively, the question of backscatter uncertainty has been addressed only minimally and hinders the quantitative use of MBES seafloor backscatter. This paper explores approaches to identifying uncertainty sources associated with MBES-derived backscatter measurements. The major sources of uncertainty are catalogued and the magnitudes of their relative contributions to the backscatter uncertainty budget are evaluated. These major uncertainty sources include seafloor insonified area (1–3 dB), absorption coefficient (up to >?6 dB), random fluctuations in echo level (5.5 dB for a Rayleigh distribution), and sonar calibration (device dependent). The magnitudes of these uncertainty sources vary based on how these effects are compensated for during data acquisition and processing. Various cases (no compensation, partial compensation and full compensation) for seafloor insonified area, transmission losses and random fluctuations were modeled to estimate their uncertainties in different scenarios. Uncertainty related to the seafloor insonified area can be reduced significantly by accounting for seafloor slope during backscatter processing while transmission losses can be constrained by collecting full water column absorption coefficient profiles (temperature and salinity profiles). To reduce random fluctuations to below 1 dB, at least 20 samples are recommended to be used while computing mean values. The estimation of uncertainty in backscatter measurements is constrained by the fact that not all instrumental components are characterized and documented sufficiently for commercially available MBES. Further involvement from manufacturers in providing this essential information is critically required. 相似文献
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This paper describes how to estimate the uncertainty of manoeuvring sea trial results without performing repeated tests using only a simulation model. The approach is based on the Monte Carlo method of uncertainty propagation. Moreover, the global sensitivity analysis procedure based on variance decomposition is described. As an example, the method is applied to estimate the uncertainty of 10°/10° zigzag overshoot angles and a 20° turning circle advance and tactical diameter for a small research vessel. The estimated uncertainty is compared with corresponding experimental uncertainty assessed from repeated tests. The method can be useful for validation studies and other studies that involve the uncertainty of sea trial results. 相似文献
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《中国海洋工程》2020,(3)
This paper presents a systematic model test program to assess the uncertainty of the ship-bank interaction forces,using the planar motion mechanism(PMM) system in a circulating water channel(CWC). Therefore, the uncertainties due to ship-bank distance and water depth are considered, and they are calculated via the partial differentials of the regression formulae based on the test data. The general part of the uncertainty analysis(UA) is performed according to the ITTC recommended procedure 7.5-02-06.04, while the uncertainty of speed is identified as the bias limit due to the flow velocity maldistribution in the CWC. In each example test for the UA of ship-bank interaction forces, 12 repeated measurements were conducted. Results from the UA show that the contribution of water depth error and flow velocity maldistribution to the total uncertainty is noticeable, and the paper explains how they increase with the change of the test conditions. The present study will be useful in understanding the uncertainty regarding the ship-bank interaction force measurement in a CWC. 相似文献
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Because of the difficulties in accurately characterizing the statistical behavior of underwater acoustic channels, tolerance to uncertain statistical modeling is an important property for underwater acoustic signal processing procedures to possess. This paper provides an overview of a number of techniques developed in recent years that can be applied to provide uncertainty tolerance in underwater signal processing applications. In addition to a discussion of general concepts of uncertainty tolerance, specific methods for attaining tolerance to uncertainty in temporal/spatial statistics for procedures such as Wiener and matched filtering, time-delay estimation, sonar system design, and signal prediction are reviewed. Tolerance to uncertainty in amplitude statistics is also a key issue in underwater channels, and techniques for achieving this goal are discussed in the contexts of signal estimation, identification, and detection procedures. 相似文献
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Prediction of coastal processes, including waves, currents, and sediment transport, can be obtained from a variety of detailed geophysical-process models with many simulations showing significant skill. This capability supports a wide range of research and applied efforts that can benefit from accurate numerical predictions. However, the predictions are only as accurate as the data used to drive the models and, given the large temporal and spatial variability of the surf zone, inaccuracies in data are unavoidable such that useful predictions require corresponding estimates of uncertainty. We demonstrate how a Bayesian-network model can be used to provide accurate predictions of wave-height evolution in the surf zone given very sparse and/or inaccurate boundary-condition data. The approach is based on a formal treatment of a data-assimilation problem that takes advantage of significant reduction of the dimensionality of the model system. We demonstrate that predictions of a detailed geophysical model of the wave evolution are reproduced accurately using a Bayesian approach. In this surf-zone application, forward prediction skill was 83%, and uncertainties in the model inputs were accurately transferred to uncertainty in output variables. We also demonstrate that if modeling uncertainties were not conveyed to the Bayesian network (i.e., perfect data or model were assumed), then overly optimistic prediction uncertainties were computed. More consistent predictions and uncertainties were obtained by including model-parameter errors as a source of input uncertainty. Improved predictions (skill of 90%) were achieved because the Bayesian network simultaneously estimated optimal parameters while predicting wave heights. 相似文献