Learning Bayesian networks using genetic algorithm

A new method to evaluate the fitness of the Bayesian networks according to the observed data is provided. The main advantage of this criterion is that it is suitable for both the complete and incomplete cases while the others not. Moreover it facilitates the computation greatly. In order to reduce the search space, the notation of equivalent class proposed by David Chickering is adopted. Instead of using the method directly, the novel criterion, variable ordering, and equivalent class are combined,moreover the proposed mthod avoids some problems caused by the previous one. Later, the genetic algorithm which allows global convergence, lack in the most of the methods searching for Bayesian network is applied to search for a good model in this space. To speed up the convergence, the genetic algorithm is combined with the greedy algorithm. Finally, the simulation shows the validity of the proposed approach.     

An evaluation method of contribution rate based on fuzzy Bayesian networks for equipment system-of-systems architecture

The contribution rate of equipment system-of-systems architecture(ESoSA) is an important index to evaluate the equipment update, development, and architecture optimization.Since the traditional ESoSA contribution rate evaluation method does not make full use of the fuzzy information and uncertain information in the equipment system-of-systems(ESoS), and the Bayesian network is an effective tool to solve the uncertain information, a new ESoSA contribution rate evaluation method based on the fuzzy...     

Ad hoc distributed mutual exclusion algorithm based on token-asking

The solution of distributed mutual exclusion is difficult in Ad hoc networks owing to dynamic topologies and mobility. Based on the analysis of the properties of Ad hoc networks and the disadvantages of the traditional algorithms, an improved Ad hoc system model was given and a novel algorithm was presented as AHDME (Ad Hoc Distributed Mutual Exclusion); it was based on the token-asking algorithms. It utilized broadcast to search for the token and to decrease the message complexity of multi-hop Ad hoc networks. Lamport's timestamp was improved to ensure the time sequence and to prevent nodes from starvation. When compared to traditional algorithms, AHDME does not require the fixed size of request queues and the global system information, which adapts itself to the frequent arrival/departures and the limited computing capability of nodes in Ad hoc networks. Performance analysis and simulation results show that the AHDME algorithm has low message complexity, small space complexity, and short response delay.     

DBS imaging based on Keystone transform

To correct the range walk through resolution cell in Doppler beam sharpening(DBS) imaging,a new DBS imaging algorithm based on Keystone transform is proposed.Without the exact values of the movement parameters and the look angle of the radar platform in the multi-targets environment,a linear transform on the received data is employed to correct different range walk values accurately under the condition of Doppler frequency ambiguity in this algorithm.This method can realize the coherent integration in azimuth dimension and improve the azimuth resolution.In order to reduce the computational burden,a fast implementation of Keystone transform is used.Theoretical analysis and simulation results demonstrate the effectiveness of the new algorithm.And through comparing the computational load of the fast implementation with several other algorithms,the real-time processing ability of the proposed algorithm is superior to that of other algorithms.     

A hypersonic target coherent integration detection algorithm based on Doppler feedback

The traversal search of multi-dimensional parameter during the process of hypersonic target echo signal coherent integration,leads to the problem of large amounts of calculation and poor real-time performance.In view of these problems,a modified polynomial Radon-polynomial Fourier transform(MPRPFT)hypersonic target coherent integration detection algorithm based on Doppler feedback is proposed in this paper.Firstly,the Doppler estimation value of the target is obtained by using the target point information obtained by subsequent non-coherent integration detection.Then,the feedback adjustment of the coherent integration process is performed by using the acquired target Doppler estimation value.Finally,the coherent integration is completed after adjusting the search interval of compensation.The simulation results show that the algorithm can effectively reduce the computational complexity and improve the real-time performance on the basis of the effective coherent integration of hypersonic target echo signals.     

Data processing of small samples based on grey distance information approach

Data processing of small samples is an important and valuable research problem in the electronic equipment test. Because it is difficult and complex to determine the probability distribution of small samples, it is difficult to use the traditional probability theory to process the samples and assess the degree of uncertainty. Using the grey relational theory and the norm theory, the grey distance information approach, which is based on the grey distance information quantity of a sample and the average grey distance information quantity of the samples, is proposed in this article. The definitions of the grey distance information quantity of a sample and the average grey distance information quantity of the samples, with their characteristics and algorithms, are introduced. The correlative problems, including the algorithm of estimated value, the standard deviation, and the acceptance and rejection criteria of the samples and estimated results, are also proposed. Moreover, the information whitening ratio is introduced to select the weight algorithm and to compare the different samples. Several examples are given to demonstrate the application of the proposed approach. The examples show that the proposed approach, which has no demand for the probability distribution of small samples, is feasible and effective.     

单线列车运行调整的梯度搜索算法仿真与研究

列车运行调整的优化是一个非常复杂的问题,需考虑的因素很多,很难给出一个完美的优化模型。根据单线列车运行调整的特点,建立了单线列车运行图的离散事件拓扑图模型,提出了＂调整运行图综合满意度＂作为运行调整的目标,并进一步论证了＂调整运行图综合满意度＂函数的单调递减特性;提出了冲突树的概念和梯度搜索算法的算法原理及搜索步骤,并实例进行仿真。仿真结果表明,该算法模型在实际运行过程中的具有较好的优化性和有效性。

Abstract：

The optimization of railway rescheduling is a very complex issue, many factors should to be taken into account, and it’s difficult to give a perfect optimization model. A discrete event topologic diagram model was derived according to the characteristics of the single-track railway diagram, and the ＂comprehensive satisfaction of the adjusted train diagram＂ was proposed as the target of the railway rescheduling, then the monotonically decreasing characteristic of the target function was demonstrated. The concept of conflict tree was developed and the principle and steps of the gradient search algorithm based on the DET model were given and simulated. The simulation results show that this algorithm has better adaptability and effectiveness in practical application.     

Novel passive localization algorithm based on weighted restricted total least square

A novel multi-observer passive localization algorithm based on the weighted restricted total least square (WRTLS) is proposed to solve the bearings-only localization problem in the presence of observer position errors. Firstly, the unknown matrix perturbation information is utilized to form the WRTLS problem. Then, the corresponding constrained optimization problem is transformed into an unconstrained one, which is a generalized Rayleigh quotient minimization problem. Thus, the solution can be got through the generalized eigenvalue decomposition and requires no initial state guess process. Simulation results indicate that the proposed algorithm can approach the Cramer-Rao lower bound (CRLB), and the localization solution is asymptotically unbiased.     

Cued search algorithm with uncertain detection performance for phased array radars

A cued search algorithm with uncertain detection performance is proposed for phased array radars. Firstly, a target search model based on the information gain criterion is presented with known detection performance, and the statistical characteristic of the detection probability is calculated by using the fluctuant model of the target radar cross section （RCS）. Secondly, when the detection probability is completely unknown, its probability density function is modeled with a beta distribution, and its posterior probability distribution with the radar observation is derived based on the Bayesian theory. Finally simulation results show that the cued search algorithm with a known RCS fluctuant model can achieve the best performance, and the algorithm with the detection probability modeled as a beta distribution is better than that with a random selected detection probability because the model parameters can be updated by the radar observation to approach to the real value of the detection probability.     

基于TDOA的无人机集群协同单目标定位

无源定位作为现代信息化战场中电子侦察的重要技术, 可以在自身不辐射电磁波的情况下实现对敌方目标的精确定位。以高灵活性、高安全性的无人机(unmanned aerial vehicle, UAV)集群为接收站, 研究基于到达时差测量的辐射源定位方法。作为高机动平台, UAV集群的位置误差更大, 基于该情况对Chan算法、Taylor算法进行改进, 并提出了一种粒子群泰勒协同的解算方法。与其他方法的定位结果进行对比, 仿真结果表明所提的方法定位精度接近克拉美罗下界(Cramer-Rao lower bound, CRLB), 解决了Taylor算法的初值问题。     

基于组合赋权的反坦克导弹武器系统作战效能评估研究

现代作战条件下反坦克导弹武器系统的作战效能评估是该类武器装备作战使用的关键,传统的评估方法主要针对该系统中某一作战分系统的效能开展研究,不能充分反映武器系统作战能力的真实性和全面性.基于此,本文针对反坦克导弹武器系统的作战效能的评估方法进行研究首先构建反坦克导弹武器效能评估指标体系,包括了指标集与评估集,并根据不同专家的意见和建议优化该指标体系;然后结合组合赋权的思想,将熵权算法与分层赋权算法所得权值加权组合构成最终权值并赋予各评价指标,从而降低评估时由于主观因素造成的误差;最后在自寻的反坦克导弹半实物仿真平台下对算法进行验证,实验结果表明了该算法的可行性.     

基于水声通信延迟的多UUV协同定位算法

针对多水下自治机器人(unmanned underwater vehicle, UUV)协同定位过程中水声通信延迟造成的定位失效问题,提出了一种基于状态估计均方误差最小的延时扩展卡尔曼滤波(delayed extended Kalman filter, DEKF)定位误差修正方法。首先建立考虑水声通信延迟的系统状态方程,利用状态转移矩阵推导系统等效量测方程,然后给出多UUV 考虑水声通信延迟的扩展卡尔曼滤波(extended Kalman filter, EKF)定位方法并分析其不足;最后在EKF方法的基础上,分析量测信息延迟对状态估计的影响,建立系统真实量测模型,设计基于状态估计均方误差最小的DEKF 算法。仿真结果表明,该方法能够有效地修正多UUV 协同定位中由于水声通信延迟造成的定位误差,在工程实践中具有一定参考意义。     

多平台信息下机动目标拦截中末制导交班研究

针对多平台信息支持下,空基探测平台等外部平台相对地基平台信息精度降低,以及数据率降低带来目标机动误差影响增大,导致防空导弹武器导引头中末制导交班概率降低的问题,建立了空基平台探测信息误差传递模型,运用“当前”统计模型和转换坐标卡尔曼滤波,对目标机动进行预测。基于目标位置预测,推导采用导引头搜索交班算法,进行了交班性能仿真。仿真结果表明,采用目标机动预测和导引头搜索算法,在信息精度和数据率降低的情况下,能够提升防空导弹武器系统中末制导交班能力。     

空间飞行器分布式通用组合导航仿真平台方案研究

在研制空间飞行器导航系统的过程中,搭建导航仿真平台能够有效地节约成本并缩短研发周期.在模块化、通用化和标准化设计原则的指导下,利用多台计算机和相应的数据总线开发了空间飞行器分布式通用组合导航仿真平台.在空间飞行器导航系统特性分析的基础上,提出了捷联惯性导航系统、GPS、脉冲星导航系统、磁强计和星敏感器组合导航方案,设计了仿真平台的结构,论述了仿真平台的硬件设计、软件开发和算法,并探讨了仿真平台的扩展性能.试验表明该仿真平台能够逼真地模拟空间飞行器导航系统,并为设计者提供有益的建议.     

T-R型双基地声纳定位算法及系统精度研究

根据T-R型双基地声纳定位的几何模型,提出利用时延-方位信息进行目标定位的双基地声纳时间方位定位(bistatic time bearing localization,BTBL)算法,并给出了算法定位误差的几何分布。通过数值仿真,研究了基线长度、时间测量误差和方位测量误差对算法定位精度的影响。仿真分析结果表明:随着基线长度增加,发射站和接收站两侧区域定位精度进一步改善,但会造成基线区的定位误差增大;在基线长度一定时,时间和方位测量误差增大均造成定位精度下降,且算法精度对方位测量误差相对敏感。与同等条件下的单基地声纳定位相比,双基地BTBL算法在接收站点具有明显的探测优势。该研究为T R型双基地系统的水下定位提供了理论依据。     

不确定条件下后装协同保障链优化调度

后装保障链是联合作战环境下的重要支撑, 针对保障链中的2个重要节点-前进基地和保障基地的资源协调问题, 提出了考虑不确定因素影响的优化模型及基于信息共享的协同保障算法; 为了解决保障数据样本较小情况下的不确定参数估算问题, 利用模糊规划方法把不确定优化模型转化为概率约束模型; 并利用增强ε-约束法来估算多目标Pareto解, 帮助后装指挥人员在难以事先给出权重的情况下选择合适的解决方案; 为了解决规划模型的计算复杂性过大的问题, 设计了嵌入自适应大规模邻域搜索的Memetic算法进行求解。最后通过仿真实验对模型和算法的有效性进行了验证。     

基于目标高斯分布的定位系统节点最优部署方法

针对三维空间定位系统中目标位置服从高斯先验分布假设条件下节点最优部署问题, 分析了纯方位目标定位算法中估计误差的费希尔信息矩阵, 推导出基于目标先验分布的克拉美罗界(Cramer-Rao bound, CRB)。为了解决目标位置在任意高斯分布时, 协方差矩阵为非对角阵的问题, 提出了基于三维坐标旋转的最大后验概率估计方法, 将协方差矩阵转化为对角阵以实现最小化CRB的迹, 从而得到定位系统中节点的最优部署。最后, 通过梯度下降算法对节点最优部署问题的理论推导进行仿真, 验证了该部署方法的有效性，同时仿真结果中不同节点部署方法的对比也表明了该方法可有效降低定位误差。     

自主式水下潜器导航仿真系统研究

基于Windows网络平台用VC 语言开发出了自主式水下潜器(简称AUV)导航仿真系统,论述了仿真系统的体系结构、网络通信和数据交换;详细介绍了仿真系统中运动载体计算机和导航设备计算机的软件实现方法和关键技术;对重力匹配和地形匹配算法也作了相应的介绍;对仿真平台进行了仿真验证分析。结果表明,该仿真系统结构合理可靠,各子系统采用的数学模型和仿真算法正确可信。该仿真系统可作为演示、验证和评估AUV导航系统正确性、有效性和实用性的先进手段和科学方法,并已得到实际应用。     

基于轨道误差搜索的双基地ISAR包络对齐算法

针对空间目标这一应用背景提出了一种基于轨道信息的双基地逆合成孔径雷达包络对齐算法。首先推导了空间目标位置预报误差与慢时间之间的函数关系,分析表明,成像时间内轨道预报误差可用慢时间的二阶函数表示。在此基础上,利用轨道预报值和轨道误差搜索结果通过在频域补偿相位的方式完成了一维距离像包络的精确对齐。参数搜索过程中,确定了误差速度和加速度的搜索步进量,并以二维图像的对比度作为代价函数。仿真结果表明,相比于传统基于回波相关性的包络对齐算法,该算法更适用于因双基地角和极化失配等因素导致信噪比较低的双基地回波。