锥形光纤在多窗口激光告警系统中的应用研究

为了实现激光告警系统的抗干扰性及宽视场,文章提出应用锥形光纤进行光学探头的设计。该方法是采用端面有锥角的光纤并与光电二极管直接耦合连接实现光电转换,通过测量电压值来表示入射光的能量。文章根据激光告警系统设计要求对锥形光纤角度选择及光纤能量接收进行了分析和实验,实验数据表明,该方法可以增大告警系统的探测视场。     

一种视觉惯性系统位姿高精度一体化标定方法

在视觉惯性定位系统中，传感器位姿关系的标定对于实现精确空间定位至关重要，针对现有标定方法对多传感器系统缺乏集成性、标定精度受限等问题，提出了一种视觉惯性系统位姿高精度一体化标定方法。通过精密三轴转台提供角度基准，基于重力矢量不变性和匀速圆周运动下向心加速度数值的一致性求解惯性测量单元（IMU）与转台之间的外参，利用转台构建控制场为相机标定提供空间角度约束，联合优化求解无重叠视场多相机内外参。仿真和实验结果表明，该方法具有较高的标定精度和稳定性，在多相机IMU系统组合定位测试中，与经典标定方法 Kalibr相比，本文方法系统运动轨迹拟合轴线的角度偏差降低40.32%，距离偏差降低18.93%，可满足高精度视觉惯性定位系统的标定需求。     

基于星点图椭圆度分布的光学系统装配误差计算方法

计算机辅助装调技术的出现大大降低了光学系统装调的难度,但是目前提出的大部分装配误差计算方法都基于波像差系数,在应用过程中还需要额外的波前传感器。基于星点图在不同视场中的椭圆度分布,提出了一种不依赖于波前传感器的装配误差计算方法,该方法只需要CCD或CMOS等图像传感器即可实现光学系统的装配误差计算。基于矢量像差理论推导了该方法的理论基础,采用椭圆度参数量化了装配误差对星点图的影响规律,揭示了椭圆度分布与装配误差之间的非线性函数关系,在此基础上,以多视场下的星点图椭圆度分布为优化目标,将光学系统的装配误差求解问题转化成多目标优化问题,可通过智能优化算法进行求解。以Hilbert 两反式光学系统为例,基于三个视场的椭圆度分布计算次镜的四个侧向装配误差,仿真结果表明该方法的计算精度可达微米级,满足实际装调需求,验证了该方法的正确性,对促进计算机辅助装调技术的工程化应用具有重要意义。     

多约束飞机设备舱布局设计方法

如何在飞机设备舱有限空间内对设备进行布局优化,并且能满足各类布局约束要求,是一个很难找到最优解的NP完全问题。将该问题抽象为三维布局问题,就此提出一种针对多类约束处理的布局设计方法,用于求解飞机设备舱布局设计问题。首先根据约束物体的可布局空间及其重要性,确定布局物体约束优先级,根据优先级高低按照一定约束矢量进行布局,其次,根据优化目标和搜索方法对无约束物体进行分类分组和预处理,模拟实际布局实现每步最优,解决无约束物体布局问题,同时采用人机结合微调布局,以达到布局的有序性和目的性。     

基于故障检测和可靠性约束的传感器布局优化

传感器布局优化是实现机电设备机内测试(BIT)系统设计优化的重要方法之一,保证系统对检测目标具有较好的检测效能是传感器布局优化的重要约束.通过测试信息模型分析,可知传感器自身可靠性问题将会影响系统效能的实现.本文在分析传感器故障概率对测试系统故障检测效能的影响的基础上,以传感器的故障概率和最小及传感器总价格最小为优化目标,以故障检测率、故障隔离率及虚警率为约束,基于系统故障——传感器的测试信息模型,设计并构建了一个传感器布局多目标优化的非线性整数规划模型(MINLP),对其求解可得到BIT系统的传感器布局优化设计方案,并以某伺服BIT系统为例进行优化设计分析.     

室内复杂区域的光源阵列优化方法研究

为了满足室内复杂区域的光源阵列布局均匀和稳定性需求,需对光源阵列优化方法进行研究。当前主要应用空间几何光学、圆锥曲线数学模型、空间矢量合成及微元化理论对室内复杂区域光源阵列进行优化布局,但存在光照均匀度较差的问题。为了节省能耗,实现光照均匀分布,提出一种基于二次规划的室内复杂区域光源阵列优化方法。首先,针对光源衰减的特性对室内复杂区域光源阵列进行分析;然后,对室内复杂区域光源阵列空间像矢量模型进行计算;最后,将室内复杂区域光源阵列优化转换为二次规划问题进行计算,实现光源阵列的布局优化。实验结果证明,所提方法能够节省能耗,实现室内复杂区域的光源阵列优化,具有广泛的应用价值。     

空间在轨激光成像雷达指标优选宏模型

凝视成像激光雷达技术是空间非合作目标位姿测量重要手段。激光雷达指标选取极大影响航天器载荷,优化选取激光雷达指标,使之既能满足空间任务需求,又能有效减少航天器载荷,减少能源消耗,意义重大。传统解决此问题的方法是通过经验选取,激光雷达指标与目标属性相容性宏模型的提出,可以为激光雷达激光输出功率、分辨率、视场角和测距精度四项指标选取提供理论依据。具体的,利用目标尺度和雷达目标距离计算雷达分辨率和视场角初值,对雷达最大可测距离进行迭代求解,为优化激光雷达发射功率提供依据。充分利用深度共生矩阵二阶参数迭代优化,确定雷达最优分辨率和视场角。最后,通过点云配准算法迭代得出测量该目标的合适的测距精度。实验结果表明,激光雷达宏模型优化选取的雷达指标满足雷达指标选择的需求。     

应用于自由空间光通信的PIN激光信号阵列接收器

针对目前的自由空间光通信存在空间光-光纤难以 有效耦合这一问题,考虑到空间光耦合进入光纤后需要将光信号转换为电信号才能实现通信 ,为此本 文提出直接将空间光信号转换为电信号的思想,设计了一种应用于空间光通信的PIN光电二 极管阵列接收器,每一个PIN光电二极管可 以独立接收空间激光并将其转换为电信号,多个PIN光电二极管通过串联和并联将电信号汇 合以方便后续信号处理。对这一新的接收器进行理论分析和模拟实验的结果表明,新的接收 器能有效提高空间光的接收效率。     

基于风险理论的主动传感器管理方法及应用研究

针对传感器资源有限的情况，以目标检测为背景，提出了一种基于风险理论的传感器管理方法.首先建立目标检测模型和传感器辐射模型，将"检测风险"和"截获风险"之和作为传感器管理风险函数，即目标函数.其次为对模型求解，将预测值的期望值作为目标函数的近似值，重新修正目标函数.接着设计了基于多Agent的分布式优化算法.仿真实验表明，通过本文提出的基于风险理论的传感器管理方法，能够有效实现传感器管理，与以往的传感器管理方法相比，本文方法更能较好地解决资源有限情况下的传感器管理问题.     

微型多道成像光谱探测列阵的设计

介绍一种新颖的微型多道成像光谱分析系统用的控制列陈。通过对探测器工作原理分析，电路及传感器元件结构的优化设计，研制出５１２位象元自扫描光电二极管阵列的２００ｎｍ－１０００ｎｍ宽米谱响应的探测器，并给出了实验结果。     

A near-optimal sensor placement algorithm to achieve complete coverage-discrimination in sensor networks

In this letter, we develop a robust and scalable algorithm to cope with the sensor placement problem for target location under constraints of the cost limitation and the complete coverage. The problem is NP-complete for arbitrary sensor fields. The grid-based placement scenario is adopted and the sensor placement problem formulated as a combinatorial optimization problem for minimizing the maximum distance error in a sensor field under the constraints. The proposed algorithm is based on the simulated annealing approach. The experimental results reveal that, for small sensor fields, the algorithm can find the optimal sensor placement under the minimum cost limitation. Moreover, it can also find a placement with minimum distance error for large sensor fields under the cost limitation.     

基于Voronoi的无线传感器网络覆盖控制优化策略

针对无线传感器网络运行状态中存在覆盖空洞的问题,提出了一种基于Voronoi有效覆盖区域的空洞侦测修复策略。该策略以满足一定网络区域覆盖质量为前提,在空洞区域内合理增加工作节点以提高网络覆盖率为优化目标,采用几何图形向量方法对节点感知范围和Voronoi多边形的位置特性进行理论分析,力求较准确地计算出空洞面积,找寻最佳空洞修复位置,部署较少的工作节点保证整个网络的连通性。仿真结果表明,该策略能有效地减少网络总节点个数和感知重叠区域,控制网络中冗余节点的存在,同时其收敛速度较快,能够获得比现有算法更高的目标区域空洞修复率,实现网络覆盖控制优化.     

大视场全天时星敏感器光学系统设计

全天时星敏感器作为星敏感器的一个发展分支,在飞机、热气球等近空间载体定姿定位方面有较好的应用前景,是GPS拒止条件下的可用导航手段。大视场全天时星敏感器相较于小视场全天时星敏感器在高精度轻小型化定姿定位方面具有较大的优势,针对近空间高度大视场全天时测星对光学系统的需求,对光学系统工作波长的选取进行了分析,利用消色差和消热差设计,实现了一种能够适应高低温环境的大视场、大相对孔径的透射式光学系统,并对像质进行了分析评价。系统工作波长为0.9～1.7μm, F/#为1.4,焦距为70 mm,视场为18°,结构总长为105 mm。试验结果表明,该光学系统具有良好的像质,能够满足大视场星敏感器白天测星要求。     

On coverage issues in directional sensor networks: A survey

The coverage optimization problem has been examined thoroughly for omni-directional sensor networks in the past decades. However, the coverage problem in directional sensor networks (DSN) has newly taken attraction, especially with the increasing number of wireless multimedia sensor network (WMSN) applications. Directional sensor nodes equipped with ultrasound, infrared, and video sensors differ from traditional omni-directional sensor nodes with their unique characteristics, such as angle of view, working direction, and line of sight (LoS) properties. Therefore, DSN applications require specific solutions and techniques for coverage enhancement. In this survey article, we mainly aim at categorizing available coverage optimization solutions and survey their problem definitions, assumptions, contributions, complexities and performance results. We categorize available studies about coverage enhancement into four categories. Target-based coverage enhancement, area-based coverage enhancement, coverage enhancement with guaranteed connectivity, and network lifetime prolonging. We define sensing models, design issues and challenges for directional sensor networks and describe their (dis)similarities to omni-directional sensor networks. We also give some information on the physical capabilities of directional sensors available on the market. Moreover, we specify the (dis)advantages of motility and mobility in terms of the coverage and network lifetime of DSNs.     

Effective sensor deployment based on field information coverage in precision agriculture

Coverage is an importance issue in wireless sensor networks. In this work, we first propose a novel notion of information coverage, which refers to the coverage efficiency of field information covered by deployed sensor nodes. On the basis of information coverage, we consider an optimization problem of how to partition the given field into multiple parcels and to deploy sensor nodes in some selected parcels such that the field information covered by the deployed sensor nodes meets the requirement. First, we develop two effective polynomial‐time algorithms to determine the deployed locations of source nodes for information 1‐coverage and q‐coverage of the field, respectively, without consideration of communication, where information q‐coverage implies that the field information in terms of information point is covered by at least q source nodes. Also, we prove the upper bound in the theoretical for the approximate solution derived by our proposed method. Second, another polynomial‐time algorithm is presented for deriving the deployed locations of relay nodes. In the theoretical, this proposed algorithm can achieve the minimized number of relay nodes. Further, the related information 1‐coverage algorithms are applied in our wireless sensor network‐based automatic irrigation project in precision agriculture. Experimental results show the major trade‐offs of impact factors in sensor deployment and significant performance improvements achieved by our proposed method. Copyright © 2013 John Wiley & Sons, Ltd.     

Compound event barrier coverage in wireless sensor network

In wireless sensor networks (WSN),more and more people utilize barrier coverage to monitor compound events.The data of compound event barrier coverage (CEBC) comes from different types of sensors.It will be subject to multi-constraints under complex conditions in real-world application.Aiming at the merging problem of compound event confidence,a computational model based on joint probability density was proposed.In order to solve the optimization problem of compound event barrier coverage under multiple complex constraints,an active set multiplier policy (ASMP) was proposed.The algorithm can calculate the coverage ratio efficiently and allocate the sensor resources reasonably in compound event barrier coverage.The algorithm can simplify complex problems to reduce the computational load of the network and improve the efficiency of the network.The simulation results demonstrate that the ASMP algorithm is more efficient in the allocation of sensor resources and network optimization.     

Worst and best-case coverage in sensor networks

Wireless ad hoc sensor networks have recently emerged as a premier research topic. They have great long-term economic potential, ability to transform our lives, and pose many new system-building challenges. Sensor networks also pose a number of new conceptual and optimization problems. Here, we address one of the fundamental problems, namely, coverage. Sensor coverage, in general, answers the questions about the quality of service (surveillance) that can be provided by a particular sensor network. We briefly discuss the definition of the coverage problem from several points of view and formally define the worst and best-case coverage in a sensor network. By combining computational geometry and graph theoretic techniques, specifically the Voronoi diagram and graph search algorithms, we establish the main highlight of the paper - an optimal polynomial time worst and average case algorithm for coverage calculation for homogeneous isotropic sensors. We also present several experimental results and analyze potential applications, such as using best and worst-case coverage information as heuristics to deploy sensors to improve coverage.     

Method for optimal allocation of network resources based on discrete probability model

The method for optimal allocation of network resources based on discrete probability model is proposed. In order to take into account multiple coverage of the monitored points, the method constructs the discrete probability perception model of the network nodes. The model is introduced into the solution of the node coverage area, and the optimized parameters of the sensor optimization arrangement are used to optimize the layout of the multimedia sensor nodes. After setting the node scheduling standard, the interaction force between the sensor nodes and the points on the curve path is analyzed by the virtual force analysis method based on the discrete probability model At the same time On this basis, the path coverage algorithm based on the moving target is used to optimize the coverage of the wireless sensor network node in order to achieve optimal configuration of network resources. The experimental results show that the proposed method has good convergence and can complete the node coverage process in a short time. The introduction of the node selection criteria and the adoption of the dormant scheduling mechanism greatly improve the energy saving effect and enhance the network resource optimization effect.

     

一种求解矩形排样问题的遗传-离散粒子群优化算法

针对制造业领域的矩形优化排样问题,提出一种遗传-离散粒子群优化算法.引入交换子和交换序概念,解决了标准粒子群优化算法在求解组合优化问题时粒子的更新难以描述问题;融合遗传算法的交叉与变异思想,增强了粒子群的多样性和稳定性;同时采用改进的最低水平线搜索算法加快算法的收敛速度,并解码形成排样方案.通过实验数据对比,验证了该算法在求解矩形排样问题中的高效性和鲁棒性.     

Design of sparse array for mad imaging based on maximizing information capacity

In past years, growing efforts have been made to the rapid interpretation of magnetic field data acquired by a sparse synthetic or real magnetic sensor array. An appealing requirement on such sparse array arranged within a specified survey region is that to make the number of sensor elements as small as possible, meanwhile without deteriorating imaging quality. For this end, we propose a novel methodology of arranging sensors in an optimal manner, exploring the concept of information capacity developed originally in the communication society. The proposed scheme reduces mathematically the design of a sparse sensor array into solving a combinatorial optimization problem, which can be resolved efficiently using widely adopted Sinmltaneous Perturbation and Statistical Algorithm （SPSA）. Three sets of numerical examples of designing optimal sensor array are provided to demonstrate the performance of proposed methodology.