通信受限下分布式多传感器协同跟踪算法

在分布式多传感器目标跟踪系统中,由于局部融合中心(LFC)的物理限制(如:有限的频率信道、处理器容量有限等),只能接收有限个传感器的传送数据。此外,信息传输的方式也将影响传感网的使用寿命,因此,研究了通信受限下的分布式多传感器目标协同跟踪问题。首先对监视区内分布的传感器进行聚类分簇形成若干个子网,接着从通信能耗的角度出发,对传感器采集信息的传递路径进行最优路径规划;进而对子网局部状态进行估计,在子网信息融合中,分别采用最大距离和、最大化信息增量两种准则进行最佳传感器选择,最后通过各子网全局航迹融合实现分布式多传感器协同跟踪。仿真验证了算法的有效性。     

多雷达多目标航迹跟踪中FMM神经网络的应用与仿真

提出了一种基于Fuzzy Min-Max (FMM)人工神经网络的多雷达多目标航迹跟踪的方法。仿真应用的实验结果表明,这种方法能够有效地完成多雷达多目标的数据融合,并比较理想地实现了多雷达多目标的航迹相关。     

一种基于Euler Spiral的缺失边界修复算法

在总结分析相关工作的基础上,提出了一种基于Euler Spiral修复认知轮廓中缺失边界的算法。该算法首先通过活动轮廓模型进行认知轮廓的初始定位,将视觉的预测性插值问题转化为中间插值问题,然后结合取向估计和Euler Spiral修复缺失的轮廓边界,取代了活动轮廓模型的迭代优化过程。对典型认知轮廓图形和遥感图像的实验结果验证了算法的有效性。     

多约束条件下无人机航路规划动态评价方法

针对多约束条件的无人机航路规划评价方法缺乏合理性和动态特性的问题,提出了基于无人机六自由度模型的飞行仿真动态评价方法。分析了无人机航路规划的约束条件和影响航路评价的因素,基于某型无人机六自由度飞行动力学模型和飞行控制系统模型建立了无人机飞行仿真系统模型,将航路规划与评价进行有机结合进而进行航路评价方法软件的设计,通过对无人机沿规划航路的仿真飞行参数进行动态特性分析,以更接近真实情况的仿真手段对多约束条件下的航路规划效果进行评价。结果表明,该方法形象直观的实现了对无人机规划航路的动态综合评价,满足工程需求。     

战时弹药输送路径PSO决策分析

介绍了粒子群优化算法的基本思想和理论,阐述了基于粒子群优化算法的战时弹药输送路径决策分析的实现过程。通过实例应用,证实了粒子群优化算法对弹药输送路经决策问题是可行和有效的。     

Solution algorithms for the parallel replacement problem under economy of scale

We consider the parallel replacement problem in which machine investment costs exhibit economy of scale which is modeled through associating both fixed and variable costs with machine investment costs. Both finite- and infinite-horizon cases are investigated. Under the three assumptions made in the literature on the problem parameters, we show that the finite-horizon problem with time-varying parameters is equivalent to a shortest path problem and hence can be solved very efficiently, and give a very simple and fast algorithm for the infinite-horizon problem with time-invariant parameters. For the general finite-horizon problem without any assumption on the problem parameters, we formulate it as a zero-one integer program and propose an algorithm for solving it exactly based on Benders' decomposition. Computational results show that this solution algorithm is efficient, i.e., it is capable of solving large scale problems within a reasonable cpu time, and robust, i.e., the number of iterations needed to solve a problem does not increase quickly with the problem size. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 279–295, 1998     

Robust shortest path planning and semicontractive dynamic programming

In this article, we consider shortest path problems in a directed graph where the transitions between nodes are subject to uncertainty. We use a minimax formulation, where the objective is to guarantee that a special destination state is reached with a minimum cost path under the worst possible instance of the uncertainty. Problems of this type arise, among others, in planning and pursuit‐evasion contexts, and in model predictive control. Our analysis makes use of the recently developed theory of abstract semicontractive dynamic programming models. We investigate questions of existence and uniqueness of solution of the optimality equation, existence of optimal paths, and the validity of various algorithms patterned after the classical methods of value and policy iteration, as well as a Dijkstra‐like algorithm for problems with nonnegative arc lengths.© 2016 Wiley Periodicals, Inc. Naval Research Logistics 66:15–37, 2019     

固定翼无人机曲线路径跟踪的积分向量场方法

常规的向量场方法在处理无人机曲线路径跟踪问题时很容易受非定常风扰的影响而使得跟踪误差增加,因此很多方法采用用无人机的惯性坐标系(地速和方位角)替代机体坐标系(空速和偏航角)的方式来提高抗风性能。但是,这种方式只能处理大小和方向均恒定的风扰,这在实际飞行中是过于理想的假设。为了克服这些不足,提出了一种采用侧偏距的积分来主动抵消非定常风扰的积分向量场方法用于固定翼无人机曲线路径跟踪控制。根据期望路径的曲率及路径角,结合无人机自身的状态信息设计了曲线路径跟踪策略,并且使用李雅普诺夫理论证明了提出的方法能够确保闭环系统的全局渐进稳定。最后,使用高性能半实物仿真系统验证了提出方法的抗风跟踪性能。     

面向卫星的在轨服务任务规划方法

针对空间在轨服务日趋成熟以及在轨服务现实需求增长的背景,以在轨服务航天器为研究对象,研究面向卫星的在轨服务任务规划问题,探讨如何合理安排与调配在轨服务资源。将问题分解为在轨服务资源分配和在轨服务路径规划两层,并建立双层优化数学模型。设计在轨服务任务规划算法求解问题,包括基于多种群并行进化的混沌遗传算法和基于全局坐标转换的NSGA-Ⅱ+GSDE算法,并通过仿真结果对比分析,验证算法的可行性和有效性。     

机器人集群路径规划技术研究现状

受社会型生物群体行为启发,群体智能得到日益广泛的关注,机器人集群作为群体智能的重要承载者得到了大量研发和广泛应用.机器人集群路径规划技术作为一项核心关键技术也得到快速发展.为此全面深入地调研了机器人集群路径规划的技术发展现状,创新性地归纳了适用于不同集群规模、可扩展性要求、通信需求以及算法要求的集群规划基础计算架构,包...