Putin – the masked nemesis of the strategy of ambiguity

Recent events demonstrate the complex and adaptive approach employed by Russia to reassert influence in Europe. The changing face of Russia’s strategy commenced in 2007 when it launched a crippling cyber-attack against Estonia. This was followed by a large Russian conventional attack against Georgia in 2008, occupying two large areas of the nation. 2014 witnessed the Russian annexation of Crimea where in just a week, Russia seized control of Crimea “without firing a shot.” The annexation of Crimea was rapidly followed by a Russian inspired and led subversive war in eastern Ukraine. The common thread among these diverse Russian operations is its use of ambiguity to confound and confuse decision makers in the West.     

一种基于部分搜索的GNSS模糊度解算方法

为解决LAMBDA算法搜索策略效率不高的问题,提出了一种基于部分搜索的模糊度解算新方法。该方法的解算成功率接近LAMBDA算法,且只需对最后3维模糊度元素采取搜索策略。同时,通过合理设定搜索椭球的大小和搜索策略;大大提高了搜索效率。通过实验对该新算法与Bootraping算法、LAMBDA算法进行了比较分析,进一步验证了该新算法的有效性。     

北斗系统三频载波相位整周模糊度快速解算

北斗导航定位系统播发三个频率观测值,有助于载波相位整周模糊度的快速、准确固定。传统的几何无关模型三频载波相位模糊度固定算法通常采用遍历整数搜索的方法确定载波相位-伪距组合系数,组合后的噪声因子较大,模糊度固定成功率不高。在分析了北斗系统伪距测量误差特性的基础上,给出了加权组合噪声因子的定义及其约束下的最优组合系数的求解方法。采用Hatch滤波提高电离层延时误差实时估计精度,成功固定三组线性无关组合系数对应整周模糊度,进而确定基础整周模糊度。利用北斗系统短基线、长基线实测数据对算法性能进行了验证,实验表明:提出的算法可优化超宽巷、宽巷组合噪声因子20%以上,模糊度固定成功率提高10%~18%左右,30s历元平滑后的基础模糊度固定成功率可达90%以上。     

一种新的星载高分辨宽测绘带SAR运动目标检测与参数估计方法

针对星载多通道高分辨宽测绘带合成孔径雷达系统,提出了一种地面运动目标检测和参数估计方法,该方法利用空时自适应处理进行杂波抑制,采用传统SAR成像处理得到模糊的运动目标图像,接着利用恒虚警检测技术检测出所有运动目标,包括真实目标和由于多普勒模糊引起的虚假目标,再根据模糊图像的空间位置关系,从所有成像目标中检测出运动目标的真实成像位置,根据运动目标的斜距历程得到因运动目标速度引起的图像位置偏移,由此估计得到运动目标速度。该方法具有运算量小、检测精度高等优点,星载仿真数据验证了本文方法有效性。     

无源时差定位系统的模糊无解问题

本文对平面三站无源时差定位系统的定位过程中可能出现的无解和模糊现象进行了探讨,找出了无解分布与布站以及观测噪声方差大小之间的规律,得出了模糊分布与布站之间的关系,并提供了一些解决方法。     

一种快速确定GPS整周模糊度的方法

GPS初始整周模糊度的求解是利用载波相位进行测量时的关键问题,采用了对系数矩阵进行QR分解的方法,用以降低矩阵的维数。模糊度搜索时,针对Z变换可能会引入多余误差,采用了对称三角分解法对协方差矩阵进行去相关处理。实验与仿真结果表明,定位误差在0.5 cm以内,方位角和仰角误差在0.1°以内。     

Minimum violations and predictive meta‐rankings for college football

This article presents two meta‐ranking models that minimize or nearly minimize violations of past game results while predicting future game winners as well as or better than leading current systems—a combination never before offered for college football. Key to both is the development and integration of a highly predictive ensemble probability model generated from the analysis of 36 existing college football ranking systems. This ensemble model is used to determine a target ranking that is used in two versions of a hierarchical multiobjective mixed binary integer linear program (MOMBILP). When compared to 75 other systems out‐of‐sample, one MOMBILP was the leading predictive system while getting within 0.64% of the retrodictive optimum; the other MOMBILP minimized violations while achieving a prediction total that was 2.55% lower than the best mark. For bowls, prediction sums were not statistically significantly different from the leading value, while achieving optimum or near‐optimum violation counts. This performance points to these models as potential means of reconciling the contrasting perspectives of predictiveness versus the matching of past performance when it comes to ranking fairness in college football. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 61: 17–33, 2014     

正反向量子斯特林循环有限时间热力学性能界限和优化准则

研究了正反向量子斯特林循环的最优性能.在经典极限下,导出了循环的有限时间热力学性能界限和优化准则.得到了斯特林热机、制冷机和热泵特性参数之间的优化关系.     

An adaptive forecasting algorithm and inventory policy for products with short life cycles

Products with short life cycles are becoming increasingly common in many industries, such as the personal computer (PC) and mobile phone industries. Traditional forecasting methods and inventory policies can be inappropriate for forecasting demand and managing inventory for a product with a short life cycle because they usually do not take into account the characteristics of the product life cycle. This can result in inaccurate forecasts, high inventory cost, and low service levels. Besides, many forecasting methods require a significant demand history, which is available only after the product has been sold for some time. In this paper, we present an adaptive forecasting algorithm with two characteristics. First, it uses structural knowledge on the product life cycle to model the demand. Second, it combines knowledge on the demand that is available prior to the launch of the product with actual demand data that become available after the introduction of the product to generate and update demand forecasts. Based on the forecasting algorithm, we develop an optimal inventory policy. Since the optimal inventory policy is computationally expensive, we propose three heuristics and show in a numerical study that one of the heuristics generates near‐optimal solutions. The evaluation of our approach is based on demand data from a leading PC manufacturer in the United States, where the forecasting algorithm has been implemented. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Optimal pricing for a short life‐cycle product when customer price‐sensitivity varies over time

Technology products often experience a life‐cycle demand pattern that resembles a diffusion process, with weak demand in the beginning and the end of the life cycle and high demand intensity in between. The customer price‐sensitivity also changes over the life cycle of the product. We study the prespecified pricing decision for a product that exhibits such demand characteristics. In particular, we determine the optimal set of discrete prices and the times to switch from one price to another, when a limited number of price changes are allowed. Our study shows that the optimal prices and switching times show interesting patterns that depend on the product's demand pattern and the change in the customers' price sensitivity over the life cycle of the product. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012