遗传算法在目标跟踪中的传感器分配算法

传感器在进行目标跟踪时,常规算法主要通过线性规划建立传感器与目标之间的分配方法.但是在对多目标和多传感器的战场环境中,这些方法有一定局限性.研究了基于遗传算法的传感器分配方法,通过构造符合传感器分配这一特殊问题的染色体,从而形成初始种群,然后利用遗传算法模拟生物遗传迭代和自然选择的遗传机理,通过多次选择最终收敛于问题的一个满意解.仿真显示,在大数据运算的环境中,该算法有更高的可行性和有效性.     

Sensor placement in active multistatic sonar networks

The idea of deploying noncollocated sources and receivers in multistatic sonar networks (MSNs) has emerged as a promising area of opportunity in sonar systems. This article is one of the first to address point coverage problems in MSNs, where a number of points of interest have to be monitored in order to protect them from hostile underwater assets. We consider discrete “definite range” sensors as well as various diffuse sensor models. We make several new contributions. By showing that the convex hull spanned by the targets is guaranteed to contain optimal sensor positions, we are able to limit the solution space. Under a definite range sensor model, we are able to exclude even more suboptimal solutions. We then formulate a nonlinear program and an integer nonlinear program to express the sensor placement problem. To address the nonconvex single‐source placement problem, we develop the Divide Best Sector (DiBS) algorithm, which quickly provides an optimal source position assuming fixed receivers. Starting with a basic implementation of DiBS, we show how incorporating advanced sector splitting methods and termination conditions further improve the algorithm. We also discuss two ways to use DiBS to find multiple source positions by placing sensors iteratively or simultaneously. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 287–304, 2017     

Optimal FCFS allocation rules for periodic‐review assemble‐to‐order systems

In Assemble‐To‐Order (ATO) systems, situations may arise in which customer demand must be backlogged due to a shortage of some components, leaving available stock of other components unused. Such unused component stock is called remnant stock. Remnant stock is a consequence of both component ordering decisions and decisions regarding allocation of components to end‐product demand. In this article, we examine periodic‐review ATO systems under linear holding and backlogging costs with a component installation stock policy and a First‐Come‐First‐Served (FCFS) allocation policy. We show that the FCFS allocation policy decouples the problem of optimal component allocation over time into deterministic period‐by‐period optimal component allocation problems. We denote the optimal allocation of components to end‐product demand as multimatching. We solve the multi‐matching problem by an iterative algorithm. In addition, an approximation scheme for the joint replenishment and allocation optimization problem with both upper and lower bounds is proposed. Numerical experiments for base‐stock component replenishment policies show that under optimal base‐stock policies and optimal allocation, remnant stock holding costs must be taken into account. Finally, joint optimization incorporating optimal FCFS component allocation is valuable because it provides a benchmark against which heuristic methods can be compared. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 158–169, 2015     

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。     

传感器组网的关键技术

传感器组网是协同作战的关键技术,从作战的动态过程角度看,传感器组网是以特定战术任务为目标,在通信技术和计算机技术支持下的战术决策。从完成特定战术任务的能力角度看,传感器管理技术、通信技术、信息融合技术以及计算机技术是影响传感器网络性能的关键因素。     

基于跟踪精度控制的多传感器管理方法

针对地面机动目标跟踪过程中的多传感器管理问题展开了研究，设计了一种基于跟踪精度控制的多传感器多目标分配方法。首先，在考虑目标与目标之间、目标与传感器之间和传感器与传感器之间等的多种约束条件下运用基于协方差控制的思想建立了多传感器多目标分配问题的优化模型；接着将等价伪量测的异步融合算法与IMM算法结合，计算各目标在不同融合周期的跟踪精度估计值；最后，以目标的跟踪精度需求为出发点，结合蚁群算法的思想，设计了一种求解所建立的多传感器多目标分配问题的优化模型的算法。仿真结果表明：该管理方法能在确保跟踪精度需求的前提下，根据对各目标跟踪任务的重要程度，合理地调度传感器资源。     

水声传感器信息处理技术

水声传感器信息融合是为潜艇、水面舰艇提供完整、准确、清晰战术态势的关键技术。结合各类声纳的特点,研究数据互联,水下被动定位与跟踪算法,纯方位系统的可观测性,跟踪坐标系的选择以及机动目标跟踪,是解决水声传感器信息处理的关键。首先对前人在这些方面的工作进行了总结和评述,然后根据现代海战的战术背景分析了水声传感器信息处理存在的一些技术难点和值得进一步研究的问题。     

Environmental regulation in project‐based industries

We study the environmental regulation of industrial activities that are organized as projects. Applications arise in construction, ship and aircraft building, and film making, among other industries. Relative to manufacturing, environmental regulation is different in project‐based industries, due to the uniqueness and geographical diversity of projects, and a lack of product takeback programs. Because the amount of waste and pollution generated by project companies can be large, regulators need environmental policies to ensure reduction of waste and pollution. We consider a regulator who attempts to maximize social welfare. We model this problem as a bilevel nonlinear program. The upper level regulator specifies waste reduction targets, which the lower level project companies meet using waste stream reduction and remediation of pollution, while attempting to control their project costs. We find that high waste diversion targets lead to outcomes with little pollution, but excessive project costs and only modest waste stream reduction. Projects that have lower task precedence density, or that have pollutants with different environmental impacts, show larger increases in project cost and time resulting from regulation. We describe a subsidy for waste stream reduction that coordinates the system, and we estimate the value of coordination. We also describe a bonus that encourages truthful reporting by project companies, and evaluate the relative cost and effectiveness of the subsidy and the bonus. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 228–247, 2015     

Sensor radiation interception risk control in target tracking

This paper is mainly on the problem of radiation interception risk control in sensor network for target tracking. Firstly, the sensor radiation interception risk is defined as the product of the interception probability and the cost caused by the interception. Secondly, the radiation interception probability model and cost model are established, based on which the calculation method of interception risk can be obtained. Thirdly, a sensor scheduling model of radiation risk control is established, taking the minimum interception risk as the objective function. Then the Hungarian algorithm is proposed to obtain sensor scheduling scheme. Finally, simulation experiments are mad to prove the effectiveness of the methods proposed in this paper, which shows that compared with the sensor radiation interception probability control method, the interception risk control method can keep the sensor scheduling scheme in low risk as well as protect sensors of importance in the sensor network.     

Route optimization for multiple searchers

We consider a discrete time‐and‐space route‐optimization problem across a finite time horizon in which multiple searchers seek to detect one or more probabilistically moving targets. This article formulates a novel convex mixed‐integer nonlinear program for this problem that generalizes earlier models to situations with multiple targets, searcher deconfliction, and target‐ and location‐dependent search effectiveness. We present two solution approaches, one based on the cutting‐plane method and the other on linearization. These approaches result in the first practical exact algorithms for solving this important problem, which arises broadly in military, rescue, law enforcement, and border patrol operations. The cutting‐plane approach solves many realistically sized problem instances in a few minutes, while existing branch‐and‐bound algorithms fail. A specialized cut improves solution time by 50[percnt] in difficult problem instances. The approach based on linearization, which is applicable in important special cases, may further reduce solution time with one or two orders of magnitude. The solution time for the cutting‐plane approach tends to remain constant as the number of searchers grows. In part, then, we overcome the difficulty that earlier solution methods have with many searchers. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Balancing a one‐way corridor capacity and safety‐oriented reliability: A stochastic optimization approach for metro train timetabling

In urban rail transit systems of large cities, the headway and following distance of successive trains have been compressed as much as possible to enhance the corridor capacity to satisfy extremely high passenger demand during peak hours. To prevent train collisions and ensure the safety of trains, a safe following distance of trains must be maintained. However, this requirement is subject to a series of complex factors, such as the uncertain train braking performance, train communication delay, and driver reaction time. In this paper, we propose a unified mathematical framework to analyze the safety‐oriented reliability of metro train timetables with different corridor capacities, that is, the train traffic density, and determine the most reliable train timetable for metro lines in an uncertain environment. By employing a space‐time network representation in the formulations, the reliability‐based train timetabling problem is formulated as a nonlinear stochastic programming model, in which we use 0‐1 variables to denote the time‐dependent velocity and position of all involved trains. Several reformulation techniques are developed to obtain an equivalent mixed integer programming model with quadratic constraints (MIQCP) that can be solved to optimality by some commercial solvers. To improve the computational efficiency of the MIQCP model, we develop a dual decomposition solution framework that decomposes the primal problem into several sets of subproblems by dualizing the coupling constraints across different samples. An exact dynamic programming combined with search space reduction strategies is also developed to solve the exact optimal solutions of these subproblems. Two sets of numerical experiments, which involve a relatively small‐scale case and a real‐world instance based on the operation data of the Beijing subway Changping Line are implemented to verify the effectiveness of the proposed approaches.     

Maintenance and flight scheduling of low observable aircraft

In this article, we focus on relatively new maintenance and operational scheduling challenges that are faced by the United States Air Force concerning low‐observable (LO) or stealth aircraft. The LO capabilities of an aircraft degrade stochastically as it flies, making it difficult to make maintenance scheduling decisions. Maintainers can address these damages, but must decide, which aircraft should be put into maintenance, and for how long. Using data obtained from an active duty Air Force F‐22 wing and interviews with Air Force maintainers and program specialists, we model this problem as a generalization of the well‐known restless multiarmed bandit superprocess. Specifically, we use an extension of the traditional model to allow for actions that require varying lengths of time, and generate two separate index policies from a single model; one for maintenance actions and one for the flying action. These index policies allow maintenance schedulers to intuitively, quickly, and effectively rank a fleet of aircraft based on each aircraft's LO status and decide, which aircraft should enter into LO maintenance and for how long, and which aircraft should be used to satisfy daily sortie requirements. Finally, we present extensive data‐driven, detailed simulation results, where we compare the performance of the index policies against policies currently used by the Air Force, as well as some other possible more naive heuristics. The results indicate that the index policies significantly outperform existing policies in terms of fully mission capable (FMC) rates. In particular, the experiments highlight the importance of coordinated maintenance and flying decisions. © 2015 Wiley Periodicals, Inc. 62:60–80, 2015     

On the optimal detection of an underwater intruder in a channel using unmanned underwater vehicles

Given a number of patrollers that are required to detect an intruder in a channel, the channel patrol problem consists of determining the periodic trajectories that the patrollers must trace out so as to maximized the probability of detection of the intruder. We formulate this problem as an optimal control problem. We assume that the patrollers' sensors are imperfect and that their motions are subject to turn‐rate constraints, and that the intruder travels straight down a channel with constant speed. Using discretization of time and space, we approximate the optimal control problem with a large‐scale nonlinear programming problem which we solve to obtain an approximately stationary solution and a corresponding optimized trajectory for each patroller. In numerical tests for one, two, and three underwater patrollers, an underwater intruder, different trajectory constraints, several intruder speeds and other specific parameter choices, we obtain new insight—not easily obtained using simply geometric calculations—into efficient patrol trajectory design under certain conditions for multiple patrollers in a narrow channel where interaction between the patrollers is unavoidable due to their limited turn rate.© 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

多传感器多目标定位与跟踪技术研究

针对炮兵打击目标的特性和获取目标信息所采用的侦察设施 ,研究了多传感器多目标定位和跟踪问题。在闭圆和聚类概念的基础上 ,提出了一种多传感器多目标融合算法 ,并给出了状态估计的最优解。仿真结果证明了这种算法的有效性。这一模型的物理实现正在进一步研究之中。     

水下传感器网络部署优化研究

水下传感器网络具有广阔的应用前景,但也存在能量有限、延迟较长、部署区域不连通和通信能耗大等问题,理论和实践证明传感器节点的优化部署是解决已上问题的有效方法。为此综合考虑水下传感器网络的工作环境及传感器特性,建立了提高网络可靠性的网络部署模型,给出了网络部署的成本函数及约束条件,并使用遗传算法对传感器节点和中转节点的部署成本及网络生命周期内的能量消耗进行优化。通过仿真实验表明,该模型收敛速度快,部署节点结果合理,达到了较好的优化网络的目的。     

Optimal maintenance policies for a safety‐critical system and its deteriorating sensor

We consider the integrated problem of optimally maintaining an imperfect, deteriorating sensor and the safety‐critical system it monitors. The sensor's costless observations of the binary state of the system become less informative over time. A costly full inspection may be conducted to perfectly discern the state of the system, after which the system is replaced if it is in the out‐of‐control state. In addition, a full inspection provides the opportunity to replace the sensor. We formulate the problem of adaptively scheduling full inspections and sensor replacements using a partially observable Markov decision process (POMDP) model. The objective is to minimize the total expected discounted costs associated with system operation, full inspection, system replacement, and sensor replacement. We show that the optimal policy has a threshold structure and demonstrate the value of coordinating system and sensor maintenance via numerical examples. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 399–417, 2017     

基于加权动态规划和航迹关联的小目标检测技术

低信噪比下运动小目标的检测一直是成像目标检测中的一个热点问题。提出了一种新的小目标检测算法,采用方向加权的动态规划算法和二值航迹关联,克服了低信噪比下目标机动和传感器的不稳定对小目标检测的影响,实现了对深空背景下运动方式任意、速度最大达1像素/帧的弱小运动目标的有效检测。     

基于Vague集的TOPSIS法求解目标优先级

针对传感器管理中目标—传感器配对出现的目标优先级求解问题,提出了一种基于Vague集的TOPSIS计算方法。在分析目标优先级的主要影响因素基础上,定义了各影响因素的影响系数。同时结合Vague集的TOPSIS法给出了目标优先级的计算步骤,为目标优先级求解提供了一种新途径。并结合仿真算例表明该方法的合理性与有效性。     

固定节点3D网格部署的水下传感器网络分簇路由算法

水下传感器网络是应用于水下通信的重要传感器网络技术。提出了基于固定节点3D网格部署的水下无线传感器网络分簇算法,设计了3D网格的编址和分簇方法,实现了基于地址分配的节点定位,构建了算法的能耗分析模型。采用MATLAB完成了算法的性能仿真,对比了DS-VBF、IAR和GEDAR 3个算法的平均数据传输延迟和网络生存时间(TTL)。实验结果表明,此算法的平均数据传输延迟较短,可明显提高UWSNS的生存时间。     

一种基于PDA滤波的多传感器管理算法

由于传感器资源或计算资源的限制,监视系统在跟踪多目标时通常不能同时为每个目标分配所有的传感器.因此,希望在满足目标跟踪性能的前提下尽可能使用较少的传感器.针对PDAF目标跟踪算法的特点,选用目标状态估计协方差的期望作为性能度量,提出了一种基于协方差控制的传感器算法.该算法通过为每个目标选择恰当的传感器组合来实现多传感器对多目标的分配.