识别无人机的无人值守光电告警系统

无人机的高速发展不仅为人类的生活带来了便利,同样也引发了各类安全问题。为此,近年来,我国重大涉密工业场所和交通枢纽为保障运行安全,积极建设了针对无人机的安防系统。光电告警系统是最重要的安防系统组件之一,其目的是识别目标和取得法律证据。介绍了一种针对无人机的无人值守光电告警系统,能够同时输出可见光和红外图像信息,并且能够自动识别目标类型。这套系统已经在我国重要的工业场所中成功应用,并取得了阶段性的成果,其成功的运行为后续智能化光电告警平台的发展奠定了基础。     

Multi-UAV reconnaissance task allocation for heterogeneous targets using an opposition-based genetic algorithm with double-chromosome encoding

This paper presents a novel multiple Unmanned Aerial Vehicles (UAVs) reconnaissance task allocation model for heterogeneous targets and an effective genetic algorithm to optimize UAVs’ task sequence. Heterogeneous targets are classified into point targets, line targets and area targets according to features of target geometry and sensor’s field of view. Each UAV is regarded as a Dubins vehicle to consider the kinematic constraints. And the objective of task allocation is to minimize the task execution time and UAVs’ total consumptions. Then, multi-UAV reconnaissance task allocation is formulated as an extended Multiple Dubins Travelling Salesmen Problem (MDTSP), where visit paths to the heterogeneous targets must meet specific constraints due to the targets’ feature. As a complex combinatorial optimization problem, the dimensions of MDTSP are further increased due to the heterogeneity of targets. To efficiently solve this computationally expensive problem, the Opposition-based Genetic Algorithm using Double-chromosomes Encoding and Multiple Mutation Operators (OGA-DEMMO) is developed to improve the population variety for enhancing the global exploration capability. The simulation results demonstrate that OGA-DEMMO outperforms the ordinary genetic algorithm, ant colony optimization and random search in terms of optimality of the allocation results, especially for large scale reconnaissance task allocation problems.     

智能空战体系下无人协同作战发展现状及关键技术

在未来复杂的战场环境下，运用多架无人机在飞行空间内构成相互协作、优势互补及效能倍增的协同作战系统，是取得智能空战胜利的关键所在。首先阐述了无人系统的定义，并分析了其内涵和分类，指出智能化是无人系统未来的发展方向，根据自主完成任务的能力进行了分级。随后引出了典型的协同作战样式，阐述了国内外协同作战发展的现状。从协同态势感知技术、交互与信息作战云技术、智能决策技术、自主攻击技术、集群协同技术及学习与进化技术等分析了制约协同作战水准的关键技术。     

Control techniques of tilt rotor unmanned aerial vehicle systems:A review

The tilt rotor unmanned aerial vehicle (TRUAV) exhibits special application value due to its unique rotor structure. However, varying dynamics and aerodynamic interference caused by tiltable rotors are great technical challenges and key issues for TRUAV's high-powered flight con-trols, which have attracted the attention of many researchers. This paper outlines the concept of TRUAV and some typical TRUAV platforms while focusing on control techniques. TRUAV struc-tural features, dynamics modeling, and flight control methods are discussed, and major challenges and corresponding developmental tendencies associated with TRUAV flight control are summa-rized.     

Obstacle avoidance for multi-missile network via distributed coordination algorithm

A distributed coordination algorithm is proposed to enhance the engagement of the multi-missile network in consideration of obstacle avoidance. To achieve a cooperative interception,the guidance law is developed in a simple form that consists of three individual components for target capture, time coordination and obstacle avoidance. The distributed coordination algorithm enables a group of interceptor missiles to reach the target simultaneously, even if some member in the multi-missile network can only collect the information from nearest neighbors. The simulation results show that the guidance strategy provides a feasible tool to implement obstacle avoidance for the multi-missile network with satisfactory accuracy of target capture. The effects of the gain parameters are also discussed to evaluate the proposed approach.     

高轨非合作目标多视线分布式相对导航方法

针对仅采用单视线难于实现高轨非合作目标的远距离自主相对导航问题,提出基于双空间机器人的多视线分布式相对导航方法。首先,建立基于多视线测量的相对导航模型,并给出空间机器人与非合作目标的相对动力学模型;然后,为降低集中式滤波相对导航的维数,设计分布式滤波的相对导航方法,采用扩展卡尔曼滤波算法实现相对运动估计;最后,建立数学仿真模型,对多视线分布式滤波相对导航算法及可观测性进行仿真校验,仿真结果表明该方法是稳定有效的。     

考虑重心位置不确定性的无尾无人机优化设计

飞机的飞行性能与重心(CG)位置密切相关,尤其是后掠式无尾飞机的重心位置对其飞行性能影响更甚,如果重心位置发生变化,升力分布随之改变,进而影响飞机航时。针对这个问题,从气动布局和设计方法两方面,设计了一种航时对重心位置不敏感的无尾无人机(UAV)。气动布局上,提出了利用螺旋桨动力配平纵向力矩的鸥翼(GW)布局,以减小重心位置变化对升阻特性的影响;设计方法上,采用稳健性优化设计(RDO)理论,分析重心位置不确定时的航时低敏感度问题。以一架小型电动无人机为研究对象,建立了无尾无人机稳健性优化设计环境,包括总体设计、代理模型构造以及稳健性优化。分析结果表明:利用螺旋桨动力配平的鸥翼布局使重心可用范围增加了5%;静安定裕度在5%~15%变化时,该布局可以有效提高航时稳健性。采用稳健性优化得到的无人机几何参数,大幅度降低了重心位置对航时的影响,显著提升了满足约束的概率。     

基于互相关矢量图的车牌定位新算法

互相关矢量图是由流场粒子图像测速的互相关计算结果绘成的矢量图形,提出一种车牌自动定位的新算法--VMLA算法,该算法基于字符笔画左右边缘之间的互相关矢量图的结构特点,可以从复杂车牌图像背景中搜索到车牌的正确位置.VMLA算法具有较强的车牌大小自适应性和实时处理能力,540幅车牌图像的实验结果初步验证了该方法的有效性.     

航空子母弹时序抛撒散布效果数值仿真(英文)

对采用时序抛撒的航空子母弹工作过程、子弹外弹道初始条件、落点散布模型进行了探讨,建立了时序抛撒外弹道初始条件模型和落点散布模型,并进行了数值仿真。根据仿真结果分析了影响落点散布的主要因素,验证了时序抛撒对改善散布效果的可行性。采用时序抛撒,并通过优化各空投参数,可使系统达到更佳的作战效能,而且可为时序抛撒机构结构设计、结构优化及散布效果分析提供理论指导。     

低雷诺数分布式螺旋桨滑流气动影响

以高空长航时（HALE）太阳能无人机（UAVs）研究为背景,采用基于混合网格技术及k-k_L-ω转捩模型求解雷诺平均Navier-Stokes（RANS）方程的多重参考系（MRF）方法,对3种螺旋桨-机翼构型的低雷诺数气动特性进行了高精度准定常数值模拟,在等拉力前提条件下,通过对比机翼气动力系数及表面流场结构特征分析了分布式螺旋桨（DEP）滑流对FX63-137机翼的气动影响。研究表明：螺旋桨滑流影响使得桨后总压及流速显著增大,这是机翼升力增大的主要原因,但同时机翼阻力特性急剧恶化,升阻比反而降低;螺旋桨滑流向机翼边界层内注入丰富湍动能从而抑制流动分离,扩大机翼表面湍流范围及附着流动区域;分布式螺旋桨滑流与低雷诺数机翼表面复杂流动相互作用显著,主要表现为滑流区域边界展向涡结构的产生。