一种改进的跳频信号频率估计算法

信号的信噪比较低时,旋转不变信号参数估计技术（Estimated Signal Parametersvia Rotational Invariance Technique,ESPRIT）算法的频率估计性能明显下降,针对这一问题,提出了一种基于ESPRIT的改进算法。该改进算法在基于ESPRIT的噪声抑制（Noise Suppressed based on ESPRIT,NS—ESPRIT）算法的基础上,利用DFT谱中的,个局部最大值点,缩小基于互相关矩阵迹模值曲线的ESPRIT算法中口的选择区域,在降低计算复杂度的同时,也有效地减弱了噪声对信号频率估计的影响。理论分析和仿真结果证明了该改进算法的可行性和有效性。     

Estimating the probability that a simulated system will be the best

Consider a stochastic simulation experiment consisting of v independent vector replications consisting of an observation from each of k independent systems. Typical system comparisons are based on mean (long‐run) performance. However, the probability that a system will actually be the best is sometimes more relevant, and can provide a very different perspective than the systems' means. Empirically, we select one system as the best performer (i.e., it wins) on each replication. Each system has an unknown constant probability of winning on any replication and the numbers of wins for the individual systems follow a multinomial distribution. Procedures exist for selecting the system with the largest probability of being the best. This paper addresses the companion problem of estimating the probability that each system will be the best. The maximum likelihood estimators (MLEs) of the multinomial cell probabilities for a set of v vector replications across k systems are well known. We use these same v vector replications to form v^k unique vectors (termed pseudo‐replications) that contain one observation from each system and develop estimators based on AVC (All Vector Comparisons). In other words, we compare every observation from each system with every combination of observations from the remaining systems and note the best performer in each pseudo‐replication. AVC provides lower variance estimators of the probability that each system will be the best than the MLEs. We also derive confidence intervals for the AVC point estimators, present a portion of an extensive empirical evaluation and provide a realistic example. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 341–358, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10019     

基于虚拟触角的自主车辆运动规划方法

在对自主车辆进行运动学分析的基础上,结合反应式行为规划方法和昆虫利用触角进行避障行走的思想,提出了一种使用圆弧形虚拟触角进行运动规划算法,并规划出在各圆弧轨迹片段车辆前轮摆角的参考值。仿真和实验结果表明：通过设置适当的初始参数,该算法能够使自主车辆在行驶过程中完全避开障碍物到达目标点,且轨迹光滑,满足车辆的运动学约束条件。该算法计算简洁、实时性强,适用于底层的实时控制,为自主车辆运动规划提供了一种简便、有效的策略。     

基于信息模型的C4ISR系统需求集成方法

多视图需求工程中"分而治之"的需求开发方式,必然会产生"需要集成"和"如何集成"等问题.研究了基于多视图的C<'4>ISR系统需求框架及其视图产品,并在此基础上给出了C<'4>ISR系统需求集成的概念与范围.通过建立需求信息模型,从语法、语义和语用三个层次研究构建一个需求集成框架.通过需求产品之间的关联关系,分析不同视图产品在集成中存在的问题,并给出了需求集成框架中不同需求产品的集成过程,为C<'4>ISR系统需求集成问题的解决提供一个可供参考的方法.     

混合粒子滤波被动定位算法

为实现空中机动单站对运动目标的快速无源定位,提出了一种基于测向交叉定位方法的混合粒子滤波算法.针对粒子滤波初始化存在的问题,该算法从测向交叉定位方法得到建议分布,利用角度测量对状态变量的约束关系产生所需粒子,避免了粒子滤波产生粒子时的随机性,减少了高维情况下所需的粒子数目,降低了运算成本,提高了粒子滤波的实时性能.与粒...     

结构振动系统的模态解耦控制

基于特征结构配置的参数化结果,给出了实现结构振动系统模态解耦的充要条件,导出了期望的反馈增益阵及闭环特征向量矩阵的全体参数化表示。该方法在实现模态解耦的同时,还提供了全部自由度,可用来实现系统设计中某些性能要求。该方法直接基于原系统的参数矩阵,便于工程应用。三级质量弹簧系统的实例表明该方法有效。     

Modeling the operation of multireservoir systems using decomposition and stochastic dynamic programming

Stochastic dynamic programming models are attractive for multireservoir control problems because they allow non‐linear features to be incorporated and changes in hydrological conditions to be modeled as Markov processes. However, with the exception of the simplest cases, these models are computationally intractable because of the high dimension of the state and action spaces involved. This paper proposes a new method of determining an operating policy for a multireservoir control problem that uses stochastic dynamic programming, but is practical for systems with many reservoirs. Decomposition is first used to reduce the problem to a number of independent subproblems. Each subproblem is formulated as a low‐dimensional stochastic dynamic program and solved to determine the operating policy for one of the reservoirs in the system. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Bounding methods for facilities location algorithms

Single- and multi-facility location problems are often solved with iterative computational procedures. Although these procedures have proven to converage, in practice it is desirable to be able to compute a lower bound on the objective function at each iteration. This enables the user to stop the iterative process when the objective function is within a prespecified tolerance of the optimum value. In this article we generalize a new bounding method to include multi-facility problems with l_p distances. A proof is given that for Euclidean distance problems the new bounding procedure is superior to two other known methods. Numerical results are given for the three methods.