基于智能算法的无人机航迹规划

文中针对多无人机在复杂约束条件下编队协同、巡航范围内覆盖率高的问题,基于K-means算法和Hop-field神经网络算法实现了一种无人机整体航迹规划方法。对任务要求的禁飞区域、目标区域建立任务区域的数字地图模型,进行模型分解合理的将有效区域分解为多个子目标点。随后采用K-means算法对无人机巡航的目标点进行聚类,并结合Hop-field神经网络算法对同类子目标点进行无人机航迹规划。以无人机在抗震救灾中的真实数据为实例,通过仿真实现了巡航区域90%的覆盖率,验证了文中方法的鲁棒性和有效性。     

不确定环境下的侦察无人机自主航路规划仿真

自主式无人机是无人机发展的必然趋势,不确定环境下的航路规划是无人机航路规划研究的新领域.为了研究战时条件下侦察无人机的自主航路规划,根据无人机的控制系统工作方式,建立了仿真模型框架,并在此基础上开展仿真研究.首先,针对战时条件下侦察无人机执行任务的不确定环境,从战场使用的实际情况出发,建立了基于目标存在概率的环境信息模型;然后,根据无人机机载探测设备探测区域建立了探测模型,提出了航路控制决策模型,并采用动态规划进行航路规划.最后,设计了一个无人机侦察不确定环境的仿真试验,仿真结果验证了该方法的有效性.     

On constructing the minimum orthogonal convex polygon for the fault-tolerant routing in 2-D faulty meshes

The rectangular faulty block model is the most commonly used fault model for designing fault-tolerant, and deadlock-free routing algorithms in mesh-connected multicomputers. The convexity of a rectangle facilitates simple, efficient ways to route messages around fault regions using relatively few or no virtual channels to avoid deadlock. However, such a faulty block may include many nonfaulty nodes which are disabled, i.e., they are not involved in the routing process. Therefore, it is important to define a fault region that is convex, and at the same time, to include a minimum number of nonfaulty nodes. In this paper, we propose an optimal solution that can quickly construct a set of minimum faulty polygons, called orthogonal convex polygons, from a given set of faulty blocks in a 2-D mesh (or 2-D torus). The formation of orthogonal convex polygons is implemented using either a centralized, or distributed solution. Both solutions are based on the formation of faulty components, each of which consists of adjacent faulty nodes only, followed by the addition of a minimum number of nonfaulty nodes to make each component a convex polygon. Extensive simulation has been done to determine the number of nonfaulty nodes included in the polygon, and the result obtained is compared with the best existing known result. Results show that the proposed approach can not only find a set of minimum faulty polygons, but also does so quickly in terms of the number of rounds in the distributed solution.     

基于UAV的移动物联网远距离通信节能策略研究

针对应急移动物联网在缺少地面基站的情况下,可靠节能地远距离传输重点区域全信息的要求,本文将无人机（Unmanned Aerial Vehicle,UAV）作为空基通信平台,研究应急移动物联网应用中大规模移动物联网设备能量受限条件下的远距离通信问题,提出基于无人机的移动物联网远距离通信节能策略.首先,对该类物联网进行系统建模;其次,根据所建模型中地面设备无序立体地分散于重点区域的特点,通过优化无人机的布署位置,在提供可靠通信的同时,降低地面设备的通信耗能;再次,根据地面设备运动性能强、活动范围广的特点,通过研究无人机与地面移动设备的联合运动策略,避免无人机频繁换簇覆盖所引起的远距离移动等大运动状态变化问题,实现无人机的移动节能.最后,通过实验,从通信耗能和运动耗能两方面验证了本文所提策略的有效性.     

Optimal Datapath Widths Within Turbo and Viterbi Decoders for High Area- and Energy-Efficiency

Datapath widths in state-of-the-art Turbo and Viterbi decoder implementations depend on estimated upper bounds of the differences of processed metrics. Aiming at highest area and energy efficiency, this paper presents guidelines for designing Turbo and Viterbi decoder datapaths with minimal widths. This is based on maximum absolute values of branch, state and path metric differences within theMax-Log-MAP respectively Viterbi decoding algorithm applying modulo normalization. The proposed methodology for determining the maximum absolute values covers punctured as well as n-input binary convolutional and Turbo codes so it accommodates higherradix add-compare-select operations. Maximum absolute values of metric differences and minimum datapath widths are presented for the 3GPP-LTE, DVB-RCS2 and IEEE-802.16 (WiMAX) compliant Turbo decoders and for the IEEE-802.11 (Wi-Fi), IEEE-802.16 (WiMAX) and 3GPP-LTE compliant Viterbi decoders. Besides, a new dynamic branch-metric saturation scheme is presented, which enables a further datapath width reduction within Turbo decoders. In total, a datapath width reduction of two bits (?20 %) is achieved applying radix-4 Max-Log-MAP arithmetic. An overall area-time-energy complexity reduction of 31% is achieved for a soft-input soft-output decoder and of 24% for the LTE Turbo decoder.     

Secrecy Energy Efficiency Maximization for UAV-Enabled Multi-Hop Mobile Relay System

To deal with the secrecy issues and energy efficiency issues in the unmanned aerial vehicles ( UAVs) assisted communication systems, an UAV-enabled multi-hop mobile relay system is studied in an urban environment. Multiple rotary-wing UAVs with energy budget considerations are employed as relays to forward confidential information between two ground nodes in the presence of multiple passive eavesdroppers. The system secrecy energy efficiency ( SEE), defined by the ratio of minimum achievable secrecy rate ( SR) to total propulsion energy consumption (PEC), is maximized via jointly optimizing the trajectory and transmit power of each UAV relay. To solve the formulated non-convex fractional optimization problem subject to mobility, transmit power and information-causality constraints, an effective iterative algorithm is proposed by applying the updated-rate-assisted block coordinate decent method, successive convex approximation (SCA) technique and Dinkelbach method. Simulation     

An optimal polygonal boundary encoding scheme in the ratedistortion sense

In this paper, we present fast and efficient methods for the lossy encoding of object boundaries that are given as eight-connect chain codes. We approximate the boundary by a polygon, and consider the problem of finding the polygon which leads to the smallest distortion for a given number of bits. We also address the dual problem of finding the polygon which leads to the smallest bit rate for a given distortion. We consider two different classes of distortion measures. The first class is based on the maximum operator and the second class is based on the summation operator. For the first class, we derive a fast and optimal scheme that is based on a shortest path algorithm for a weighted directed acyclic graph. For the second class we propose a solution approach that is based on the Lagrange multiplier method, which uses the above-mentioned shortest path algorithm. Since the Lagrange multiplier method can only find solutions on the convex hull of the operational rate distortion function, we also propose a tree-pruning-based algorithm that can find all the optimal solutions. Finally, we present results of the proposed schemes using objects from the Miss America sequence.     

Hybrid formation control of the Unmanned Aerial Vehicles

An essential issue in the formation control of Unmanned Aerial Vehicles (UAVs) is to design a reliable controller in their path planner level to handle all interactions between the continuous dynamics of the system and inherent discrete nature of the decision making unit, which has been embedded to coordinate the control submodules. In this paper, we have proposed a new approach of hybrid supervisory control of UAVs for a two-dimensional leader follower formation scenario. The approach is able to comprehensively capture internal relations between the path planner dynamics and the decision making unit of the UAVs. To design such a hybrid supervisory controller for the formation problem, we have introduced a new method of abstraction, based on polar partitioning of the state space. Furthermore, we have utilized the properties of multi-affine vector fields over the polar partitioned space. Within this framework, we design a modular decentralized supervisor in the path planner level of the UAVs to achieve two major goals: first, reaching the formation and second, keeping the formation. In addition, an inter-collision avoidance mechanism has been considered in the controller structure. The approach is robust against uncertainty in the initial state of the system, in the sense that it can bring the follower UAV to the desired position, starting from any arbitrary initial position inside the control horizon. Moreover, the velocity bounds are applied through the design procedure so that the generated velocity references can be given to the lower level of the control hierarchy, as the references to be followed.     

不确定环境下多无人机协同搜索算法研究

不确定环境下多无人机协同搜索是多无人机协同控制的一个重要研究内容。多架无人机同时对一个不确定区域进行搜索,目的在于获取搜索区域的信息,降低环境的不确定度,并尽可能发现隐藏在环境中的目标。针对这一问题,提出一种基于协同进化算法的多无人机协同区域搜索算法。首先,建立搜索概率图来描述搜索环境的不确定性,并使用贝叶斯准则更新搜索概率图,然后,使用协同进化算法,在线生成多UAV协同搜索的路径。仿真结果验证了算法的有效性。     

优化TSP算法的完善及推广

本文完善和推广了文献１中的简单多边形优化三角剖分算法，提出了一种一般化的算法，它能对卷曲，缠绕复杂的简单多边形进行优化三角剖分。我们还把这种算法推广到简单多边形的优化外三角剖分和任意嵌套封闭多边形的情形。     

基于注意力机制ConvLSTM的UAV节能预部署策略

无人机(UAV)可以作为空中基站而凭借其移动性灵活地实现热点区域的覆盖.如何预测流量的分布而优化UAV部署是运营商面临的挑战.针对此问题,该文提出一种基于注意力机制卷积长短期记忆网络(A-ConvL-STM)的UAV节能预部署策略:提出一种融合注意力机制的卷积长短期记忆深度时空网络模型A-ConvLSTM,用于预测用户...     

A new linear convex hull algorithm for simple polygons (Corresp.)

A new optimal algorithm for computing the convex hull of a simple polygon in the plane, along with a proof of correctness, is presented. The main novelty of the proposed algorithm is its use of existing concepts such as the unimodality of the area of a triangle inscribed in a convex polygon and Sldansky's scan. The combination of these concepts gives us new insight into the problem.     

Coverage optimization algorithm based on VF-CS in mobile sensor network

A random placement of large-scale sensor network in the outdoor environment often causes low coverage.An area coverage optimization algorithm of mobile sensor network (MSN) based on virtual force perturbation and Cuckoo search (VF-CS) was proposed.Firstly,the virtual force of the sensor nodes within the Thiessen polygon was analyzed based on the partitioning of Voronoi diagram of the monitoring area.Secondly,the force of polygon vertices and neighbor nodes was taken as the perturbation factor for updating the node’s location of the Cuckoo search (CS).Finally,the VF-CS guided the node to move so as to achieve the optimal coverage.The simulation results demonstrate that the proposed algorithm has higher coverage and shorter average moving distance of nodes than the Voronoi diagram based algorithms in literatures.     

5G异构超密度网络中吞吐量与覆盖的联合优化

为了权衡5G异构超密度网络(Heterogeneous Ultra-Dense Networks,HUDN)中系统吞吐量最大化与覆盖优化间的冲突,提出基于功率控制的吞吐量和覆盖的联合优化(CJTC)算法.首先,推导系统吞吐量最大化的目标函数,再通过凸优等式转换,求解实现吞吐量最大化的基站发射功率;然后,推导切换失败率最...     

高速公路场景中车用自组织网络的节点度

该文基于大尺度路径损耗无线传播模型将高速公路场景中的车用自组织网络(VANET)建模为几何随机图,提出了VANET有效组网面积的概念,分析说明了VANET的准线性拓扑特点,并基于交通流理论关于自由流条件下的车头时距分布,推导得出了无线传输范围内至少存在k个邻居的概率计算方法。实验结果表明:该文提出的概率描述思想是一种适合计算高速公路场景中车辆网络节点度的有效方法。     

基于Direct3D电子海图区域绘制方法

介绍了一种基于Direct3D在海图中绘制随机凸边形半透明效果的方法。首先分析采取依次填充多边形顶点缓冲区的方法引起的问题,并针对此问题介绍了格雷厄姆扫描法（Graham算法）构建凸多边形,最后阐述了整个软件的处理流程、场景渲染及其实现效果。     

一种有效的超声宽景成像方法研究

宽景成像技术可以得到视野范围更大的图像。本文使用基于SAD匹配准则的图像配准技术来获得运动向量，使用连续图像拼接方法进行图像的融合。并提出利用运动向量校正来提高向量精度，采用多遗形填充方法改进图像的质量。最后，通过实验证明该方法用于宽景成像是有效的。     

四旋翼无人机的轨迹规划跟踪控制研究

针对四旋翼无人机的实际应用需求，开展轨迹跟踪控制研究。提出了一种基于快速扩展随机树（RRT）算法的Dubins航迹规划方法，同时搭建了四旋翼模型，并设计了轨迹跟踪控制方案对所提出的规划路径进行了轨迹跟踪仿真。该RRT-Dubins算法采用RRT算法对有障碍区域的无人机路径进行有效规划，然后利用Dubins路径对规划出的轨迹进行平滑处理，以形成一条无人机可飞行路径。仿真实验表明，采用所提出的轨迹规划方法及路径可以较好地规避障碍区域，且轨迹平滑更适合无人机飞行，同时验证了所提轨迹跟踪控制方案的有效性。     

基于线性光谱混合模型的地表温度像元分解方法

以北京市Landsat TM为数据源,提出了一种新的地表温度光谱分解模型(Temperature Unmixing with Spectral,TUS),以期将地表温度的空间分辨率提高到30 m.首先,基于线性光谱混合模型获得地表组分的丰度值.然后,基于温度/植被指数选取典型端元的地表温度.最后,综合地表组分的比辐射率数据实现地表温度的分解.结果表明,TUS模型能够有效地提高地表温度的空间分辨率,反映不同地表组分地表温度的空间差异性,平均绝对误差(MAE)和均方根误差(RMSE)分别为1.25 K和2.27 K,非常适合于复杂地表覆盖地区的地表温度降尺度处理.     

Robust Audio Watermarking Algorithm Based on Empirical Mode Decomposition

A novel robust audio watermarking algorithm based on empirical mode decomposition is proposed.The intrinsic feature of the final residual decomposed from the audio frame is selected to embed watermark and the algorithm works by shifting each element of the final residual to make its sum greater or less than 0.The experimental results show that the proposed algorithm does not change the property of the final residual after embedding watermark and the watermark is robust against various kinds of attacks.Compared with existing classic algorithms based on Empirical mode decomposition (EMD),the proposed algorithm largely improves both the robustness and imperceptibility of watermarking.