A standardized scan statistic for detecting spatial clusters with estimated parameters

The scan statistic based on likelihood ratios (LRs) have been widely discussed for detecting spatial clusters. When developing the scan statistic, it uses the maximum likelihood estimates of the incidence rates inside and outside candidate clusters to substitute the true values in the LR statistic. However, the parameter estimation has a significant impact on the sensitivity of the scan statistic, which favors the detection of clusters in areas with large population sizes. By presenting the effects of parameter estimation on Kulldorff's scan statistic, we suggest a standardized scan statistic for spatial cluster detection. Compared to the traditional scan statistic, the standardized scan statistic can account for the varying mean and variance of the LR statistic due to inhomogeneous background population sizes. Extensive simulations have been performed to compare the power of the two cluster detection methods with known or/and estimated parameters. The simulation results show that the standardization can help alleviate the effects of parameter estimation and improve the detection of localized clusters. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

基于Kullback-Leibler距离离散度的加权代理模型

复杂系统的仿真通常具有高维度、高计算量等特点，代理模型因其明晰的数学表达和良好的计算特性可用于逼近真实系统。加权模型对比单个代理模型来说，其稳定性和适应性更广。不同的代理模型其性能不一，根据特定指标，可以构造最优加权代理模型。基于代理模型预测分布以及Kullback-Leibler距离构造各子代理模型之间的离散度，并提出一种新的权函数构造方法。算例表明，该方法与最优子模型的精度相当，同时能提高对真实响应分布的逼近。     

GBAS中抑制电离层异常的改进自适应Hatch滤波算法

针对单频地基增强系统(Ground Based Augmentation System, GBAS)中电离层异常时Hatch滤波器平滑精度降低问题,系统分析了电离层延时对Hatch滤波器平滑精度的影响,提出一种改进自适应Hatch滤波算法。根据卫星信号计算码载偏离度,并利用二阶线性时不变低通滤波器抑制码载偏离度高频信号,以实现电离层异常实时检测;建立平滑后伪距误差均方根与电离层延时变化率、伪距测量噪声标准差以及平滑时间三者之间的函数模型,并由此确定出Hatch滤波器最优平滑时间。利用GBAS原理样机进行验证实验,结果表明:自适应Hatch滤波算法能够根据卫星信号电离层延时变化率确定滤波器最优平滑时间,且当电离层异常时,自适应Hatch滤波器机载位置误差最大由1.15 m减小为0.43 m,从而验证了所提算法的有效性。