Novel cued search strategy based on information gain for phased array radar

A search strategy based on the maximal information gain principle is presented for the cued search of phased array radars. First, the method for the determination of the cued search region, arrangement of beam positions, and the calculation of the prior probability distribution of each beam position is discussed. And then, two search algorithms based on information gain are proposed using Shannon entropy and Kullback-Leibler entropy, respectively. With the proposed strategy, the information gain of each beam position is predicted before the radar detection, and the observation is made in the beam position with the maximal information gain. Compared with the conventional method of sequential search and confirm search, simulation results show that the proposed search strategy can distinctly improve the search performance and save radar time resources with the same given detection probability.     

基于智能虚拟环境的地铁站台仿真系统

实现了一个用于列车驾驶培训的地铁站台仿真系统.系统由一个可被感知的站台虚拟环境和虚拟乘客系统组成.站台环境由静态场景、动态场景两部分组成,可在用户控制下发生变化.虚拟乘客通过感知站台环境的变化做出行为判断与动作.乘客仿真模型采用分层结构,分别实现环境感知、决策、行为选择、动作实现与实时绘制.目前,该系统已用于地铁列车仿真器,成为培训司机站台操作的工具.     

Efficient combination rule of Dezert-Smarandache theory

The Dezert-Smarandache theory （DSmT） is a useful method for dealing with uncertainty problems. It is more efficient in combining conflicting evidence. Therefore, it has been successfully applied in data fusion and object recognition. However, there exist shortcomings in its combination rule. An efficient combination rule is presented, that is, the evidence＇s conflicting probability is distributed to every proposition based on remaining the focal elements of conflict. Experiments show that the new combination rule improves the reliability and rationality of the combination results. Although evidences conflict another one highly, good combination results are also obtained.     

基于新息序列修正的输入估计算法

针对传统输入估计算法跟踪机动目标时检测概率和估计精度不高的缺点,提出一种改进的输入估计跟踪算法。算法利用对检测窗内新息序列进行修正以及对卡尔曼滤波状态变量进行补偿的方法,消除了已有机动检测估计对后继机动输入估计的影响,提高了对机动的检测概率和估计精度。理论分析和仿真结果表明,改进后的算法相比原有算法和IMM3算法,不仅跟踪性能有显著提高,而且对加速度缓变的机动也有较好的跟踪能力。     

Knowledge-based bridge detection from SAR images

Automatic bridge detection is an important application of SAR images. Differed from the classical CFAR method, a new knowledge-based bridge detection approach is proposed. The method not only uses the backscattering intensity difference between targets and background but also applies the contextual information and spatial relationship between objects. According to bridges’ special characteristics and scattering properties in SAR images, the new knowledge-based method includes three processes: river segmentation, potential bridge areas detection and bridge discrimination. The application to AIRSAR data shows that the new method is not sensitive to rivers’ shape. Moreover, this method can detect bridges successfully when river segmentation is not very exact and is more robust than the radius projection method.     

Study on the extending multi-attribute decision model of grey target

Based on the distance of interval numbers and the two-stage decision methods, this paper expands the decision model of grey target into some situation under which the decision information and target weights are the interval numbers at the same time. It also gives the optimization method of weights in the grey target. We get the optimum coordinated vector utilizing the combination assigning method, based on the local optimization of various schemes. So it can shift the weights of interval number into real number form and sequence it according to the weighted off-target distance. Finally the effectiveness and practicality of the model is proved by a real project.     

Testing serial correlation in semiparametric varying coefficient partially linear errors-in-variables model

The authors propose a V _{N, p} test statistic for testing finite-order serial correlation in a semiparametric varying coefficient partially linear errors-in-variables model. The test statistic is shown to have asymptotic normal distribution under the null hypothesis of no serial correlation. Some Monte Carlo experiments are conducted to examine the finite sample performance of the proposed V _{N, p} test statistic. Simulation results confirm that the proposed test performs satisfactorily in estimated size and power. This research is supported by the National Natural Science Foundation of China under Grant Nos. 10871217 and 40574003; the Science and Technology Project of Chongqing Education Committee under Grant No. KJ080609; the Doctor's Start-up Research Fund under Grant No. 08-52204; and the Youth Science Research Fund of Chongqing Technology and Business University under Grant No. 0852008.     

Model and algorithm of flow interception problem with multi-type of flows

To study simultaneous location of different kinds of facilities, a new model of flow interception problem with multi-type of flows is proposed, with the consideration of multi-purpose flows and the influence of facilities on each other. To be more practical, the objective is to maximize the benefits from flow-by customers instead of maximizing flows in the past. Since this problem is NP-hard and there is no optimal solution for large network, greedy and improved greedy heuristic algorithms are proposed. A computational example is presented to show that the optimal location decisions are proved to be strongly dependent on the influence coefficients and average profits by one customer and different types of facilities are almost co-located. Finally the results of sensitivity analysis are reported.     

基于复杂网络的军事通信网络建模与性能分析

针对军事通信体系的复杂性和网络化结构特点,通过分析体系中装备实体及各装备之间的通信关系,抽取通信网络模型的构建要素,提出军事通信网络图结构模型。在此基础上设计基于图论的测度指标,分别从装备实体重要性、链路通信重要性以及网络抗毁性3个层次分析军事通信网络的性能。最后,通过具体实例对所提模型及评价方法的可行性进行检验,为战场复杂体系建设提供理论依据。     

Credit Scoring Based on the Set-Valued Identification Method

Credit scoring is one of the key problems in financial risk managements. This paper studies the credit scoring problem based on the set-valued identification method, which is used to explain the relation between the individual attribute vectors and classification for the credit worthy and credit worthless lenders. In particular, system parameters are estimated by the set-valued identification algorithm based on a given recognition criteria. In order to illustrate the efficiency of the proposed method, practical experiments are conducted for credit card applicants of Australia and credit card holders from Taiwan, respectively. The empirical results show that the set-valued model has a higher prediction accuracy on both small and large numbers of data set compared with logistic regression model. Furthermore, parameters estimated by the set-valued identification method are more stable,which provide a meaningful and logical explanation for extracting factors that influence the borrowers' credit scorings.