低轨卫星初始状态误差对反演地球重力场的影响

基于动力学法反演地球重力场的基本理论,研究了卫星初始状态向量误差对应用低轨卫星精密轨道数据反演地球重力场的影响。在仅考虑低轨卫星初始状态误差的情况下进行了模拟计算,结果表明:在利用低轨卫星精密轨道数据反演地球重力场时,卫星初始状态向量误差需要重新进行估计;在目前的轨道精度水平下,若不顾及误差方程二次项的影响,反演弧长不宜过长;卫星初始状态速度误差(约1.5mm/s)的影响要大于位置误差(约10 cm)的影响。     

跨海大桥高程基准统一新方法研究

提出基于高程异常差的GPS跨海水准新方法,给出新方法的基本原理和数据处理方案,对用垂线偏差、神经网络法、支持向量机求解高程异常差方法的精度和实用范围作计算分析.结果表明:基于垂线偏差的高程异常差拟合方法适用于距离约5 km的高程传递.基于支持向量机的高程异常差拟合方法,在平原地区,当GPS和水准重合点的点数较多、点位分布较合理时,跨距可以达到30 km.而基于神经网络进行高程异常差拟合适用于距离约10 km的高程传递.     

一种自适应匹配子空间亚像元目标探测方法

为了克服基于线性混合模型的高光谱遥感影像亚像元目标探测方法的缺陷, 提出了一种基于全限制性线性分解的自适应匹配子空间探测方法。首先利用交叉相关光谱匹配技术求得各个像元所含端元类别信息, 然后根据端元类别信息和全限制性分解的结果构造自适应匹配子空间探测算子, 利用端元类别信息在探测中动态选择端元, 降低端元数目估计偏差对探测结果的影响, 提高探测器对目标与背景的可分性。实验证明, 该方法与其他基于线性混合模型的亚像元目标探测方法相比, 可以更好地克服端元数目估计偏差对探测结果的影响, 无论是端元个数低估还是     

基于GPS软件接收机的抗窄带干扰方法

针对硬件接收机中传统抗干扰方法成本高、体积大、功率大和环境受限等问题,提出了用GPS软件接收机作为抗干扰算法研究平台,用子空间分解的时域滤波法和频域滤波法消除窄带干扰,其中频域滤波法中干扰频率分量置零有时会引起信号在时域波形畸变。为了解决该问题,提出了用广义延拓插值法,得到干扰频带去除干扰后的广义延拓插值估计信号。实验仿真结果表明,两种方法都能有效而可靠地去除窄带干扰,基于广义延拓插值的频域滤波法更显其优越性。     

基于Gabor变换和支持向量机的手写体字符识别算法

针对在手写字符识别中由于书写习惯和风格的不同造成字符模式不稳定的问题,将支持向量机SVM方法用于手写字符的识别.算法首先采用Gabor变换提取手写字符图像的特征参数,然后采用提取的特征训练SVM分类器.再应用SVM分类器分类和判别手写字符.实验表明这种方法具有良好的车牌识别效果,较强的鲁棒性,较大的应用价值.     

Extending self-organizing maps for supervised classification of remotely sensed data

An extended self-organizing map for supervised classification is proposed in this paper. Unlike other traditional SOMs, the model has an input layer, a Kohonen layer, and an output layer. The number of neurons in the input layer depends on the dimensionality of input patterns. The number of neurons in the output layer equals the number of the desired classes. The number of neurons in the Kohonen layer may be a few to several thousands, which depends on the complexity of classification problems and the classification precision. Each training sample is expressed by a pair of vectors ： an input vector and a class codebook vector. When a training sample is input into the model, Kohonen＇s competitive learning rule is applied to selecting the winning neuron from the Kohouen layer and the weight coefficients connecting all the neurons in the input layer with both the winning neuron and its neighbors in the Kohonen layer are modified to be closer to the input vector, and those connecting all the neurons around the winning neuron within a certain diameter in the Kohonen layer with all the neurons in the output layer are adjusted to be closer to the class codebook vector. If the number of training sam- ples is sufficiently large and the learning epochs iterate enough times, the model will be able to serve as a supervised classifier. The model has been tentatively applied to the supervised classification of multispectral remotely sensed data. The author compared the performances of the extended SOM and BPN in remotely sensed data classification. The investigation manifests that the extended SOM is feasible for supervised classification.     

Sequence analysis and quantitative detection of Norwalk-like viruses in cultured oysters of China

We isolated 4 Norwalk-like viruses (NLVs) contaminated oysters from 33 Chinese oysters collected from local commer-cial sources of Shandong Province. After amplification of the RNA-dependent RNA polymerase (RdRp) region of NLVs genomes with RT-PCR, the open reading frame 1 (ORF1) of the RdRp was sequenced and subjected to multiple-sequence alignment. The re-suits showed that NLVs in the four isolates belong to genogroup Ⅱ. The sequence comparison showed that the similarity between four Chinese oyster isolates were higher than 99.0%, which indicated that NLVs prevalent in close areas have high homogeneity in genome sequences. In addition, the most conserved sequences between diverse NLVs were used to design primers and TaqMan probes, then the real-time quantitative PCR assay was performed. According to the standard curve of GII NLVs, the original amounts (copies) of NLVs in positive patient's fecal isolate, positive Japanese oyster isolate, and the Chinese oyster isolate were 8.9×108, 1.25×108 and 4.7×101 respectively. The detecting limit of NLVs was 1×101 copies. This study will be helpful for routine diagnosis of NLVs pathogens in foods and thus for avoiding food poisoning in the future.     

基于集合预报极端天气预测指数的浙江分类强对流预报模型

利用2016—2021年ECWMF集合预报资料、浙江自动站实况资料等,计算浙江短时强降水、雷暴大风和冰雹等强对流天气相关物理量的极端天气预报指数（EFI：Extreme Forecast Index）,分析EFI分布特征,并构建了分类强对流预报模型。结果表明：强对流天气与物理量的EFI有密切联系,发生短时强降水时,对流有效位能、整层可降水量、850 hPa与500 hPa温差和位温差的EFI较大,而垂直风切变的EFI为负值,因而较小的垂直风切变更有利于出现极端降水;发生雷暴大风和冰雹时,对流有效位能、850 hPa与500 hPa温差和位温差以及850 hPa温度露点差的EFI较大,700 hPa露点温度的EFI为负值,与上层干冷下层暖湿的有利层结条件有关。利用支持向量机多分类方法,将强对流天气相关物理量的EFI作为特征值开展训练,构建的预报模型对于非局地强对流天气有较好的预报效果,其中短时强降水的误判率明显低于雷暴大风。     

预测华北地区年度地震趋势的支持向量机分类方法

以太阳黑子数、地球自转速率变化数据和全球7级以上地震应变释放量作为预测因子,使用支持向量机分类方法建模预测中国华北地区年度地震强度,预测准确率为0.93,表明该方法具有较好的预测效果.