基于数字式红外传感器的姿态测量盲区补偿法

单轴红外姿态测量系统在测量小型无人机姿态角时存在盲区,通过增加一组与原轴线相垂直的红外传感器,形成双轴姿态测量系统,对盲区进行补偿。两组红外传感器一定有一组位于倾角可测区域,通过测试目标轴的输出温差的大小,判断位于可测区域的轴线,可实现对目标轴姿态角的解算。首次采用数字式输出红外热电堆传感器设计实现了180°无盲区的姿态角测量模块,经过测试,其静态误差小于2°。     

基于一致性的小型四旋翼机群自主编队分布式运动规划

设计一种小型四旋翼无人机群起飞后自主形成正多边形编队的分布式运动规划方法.在四旋翼无人机的串级控制系统框架下,分布式编队控制器以简化agent模型为基础,同时采用平均一致性算法和有领导一致性算法,共同产生各无人机位置与偏航角的期望轨迹.讨论了达成最终协调目标队形的拓扑条件,并给出一种基于有向Hamilton环的通信拓扑设计方案.最后通过数值仿真验证了所提出算法的有效性.     

攻击型无人机鲁棒导引律研究

文章研究了攻击型无人机鲁棒导引系统,采用对干扰和摄动具有自适应能力的滑动模态变结构控制方法设计了攻击型无人机滑模导引规律.针对用于消除颤振的伪滑动模态不能实现精确跟踪的缺陷,对滑模导引规律中颤振消除进行了优化设计,引入系统运动状态轨迹接近角变量,使消除颤振的伪滑动模态边界层宽度随着系统状态到达滑动模态而逐渐减小为零,从而达到了既能消除颤振又能实现精确跟踪的设计目标.通过仿真验证了该导引规律具有攻击弹道平缓、抗目标机动扰动能力强、鲁棒性好、制导精度高的优点.     

无人机上行链路数据传输方案

为保证无人飞机在动态环境下数据传输的稳定性和可靠性,提出了一种循环正交M元扩频上行链路数据传输方案。按此方案传输数据,发送信号不存在潜在的周期性,系统的抗干扰和抗截获性能得到了很好的保障。在动态环境中,由于载体具有较大的加速度,载波多普勒频移剧烈变化,普通接收机载波跟踪环极易失锁,故提出一种基于经验值查表的载波跟踪算法,在锁频环内引入经验值查找表,环路能自适应调整环路滤波器带宽,从而实现任意时刻的高精度载波跟踪。     

自动化综采工作面概念探讨

介绍了国内自动化综采工作面的技术现状,并将综采工作面的设备分为生产设备、辅助设备、测控系统;针对目前业内工作面名称混乱的情况,认为"自动化综采工作面"的命名比较恰当;提出了自动化综采工作面技术可划分为综采工作面局部自动化、综采工作面半自动化、综采工作面全自动化、综采工作面智能自动化4个等级并给出了具体特征;介绍了自动化综采工作面的发展途径,指出把自动化综采工作面看成是一台可以自动行走、自动割煤、自动支护、自动装煤、自动运煤的大型机器更符合实用要求。     

Biologically adaptive robust mean shift algorithm with Cauchy predator-prey BBO and space variant resolution for unmanned helicopter formation

Visual tracking technology can provide measurement information for unmanned helicopter formation and thus, more attention is being paid to this research area. We propose a novel mean shift （MS） algorithm that is both adaptive and robust for unmanned helicopter formation and apply it to the leading unmanned helicopter tracking. The movement of an unmanned helicopter is very flexible and changeable, which makes the tracking there of more difficulty than for common targets. In creating an algorithm that can adapt to the acceleration of the unmanned helicopter and estimates both the scale and orientation of the movement changes, we combine the traditional MS with the bio-inspired Cauchy predator-prey biogeography-based optimization （CPPBBO） evolutionary algorithm, and also the space variant resolution （SVR） mechanism of the human visual system （MS-CPPBBO-SVR）. To demonstrate the effectiveness and robustness of the proposed method and justify the importance of the CPPBBO algorithm and SVR mechanism at the same time, a series of comparative exper- iments were carried out. The experimental results of the proposed MS-CPPBBO-SVR method are compared with other competitive tracking methods, such as MS, MS with SVR （MS-SVR）, MS-SVR with several other optimization algorithms, and the robust particle filter algorithm. The experimental results demonstrate that our proposed tracking approach, MS-CPPBBO-SVR, is more adaptive, robust and efficient in target tracking than the other methods.     

无人机群目标搜索的主动感知方法

为提升蚁群搜索算法在规模大的栅格环境中对未知目标的搜索效率,提出基于蚁群算法的主动感知搜索框架。该框架通过应用历史环境信息来选择无人机的运动方式,并由无人机运动方式和感知域信息得到新的环境信息,从而实现无人机群的智能自动化搜索功能。新方法计算出一种具有探索偏好的未搜索概率,可使无人机搜索时偏向未搜索程度高的栅格,以此来提高算法的搜索能力。同时,以未搜索概率和信息素作为运动方式决策的依据来建立一种新的运动方式选择机制。该机制不仅考虑了目标可能出现的区域,又可兼顾未知区域,从而可实现无目标先验信息条件下的搜索过程。仿真结果表明,此算法在规模大的栅格环境中,与现有算法相比具有更高的搜索效率,并且得到的目标分布信息将更加全面。     

禁飞区无人机预警算法研究

针对大量在空中无秩序飞行的无人机有可能会闯入飞机场等禁飞区的情况,为了避免发生空中交通安全事故,提出了一种无人机禁飞区预警算法。首先,该算法经过坐标变换将描述无人机位置点的GPS坐标转换成对应的平面坐标;接着,采用改进的最小二乘曲线拟合算法预测出无人机的飞行轨迹;然后,通过计算预测的飞行轨迹曲线在当前点的切线是否会与描述禁飞区的电子围栏相交,来判断无人机是否会进入禁飞区。同时,所有的无人机都会安装上飞行数据记录模块,来实时地为该算法提供无人机的飞行状态信息。最后,通过MATLAB仿真实验验证了该预警算法的可行性和有效性,表明该算法可以对禁飞区周围的无人机进行预警。     

Adaptive key SURF feature extraction and application in unmanned vehicle dynamic object recognition

A new method based on adaptive Hessian matrix threshold of finding key SRUF( speeded up robust features) features is proposed and is applied to an unmanned vehicle for its dynamic object recognition and guided navigation. First,the object recognition algorithm based on SURF feature matching for unmanned vehicle guided navigation is introduced. Then,the standard local invariant feature extraction algorithm SRUF is analyzed,the Hessian Metrix is especially discussed,and a method of adaptive Hessian threshold is proposed which is based on correct matching point pairs threshold feedback under a close loop frame. At last,different dynamic object recognition experiments under different weather light conditions are discussed. The experimental result shows that the key SURF feature abstract algorithm and the dynamic object recognition method can be used for unmanned vehicle systems.     

An optimization model of UAV route planning for road segment surveillance

Unmanned aerial vehicle （UAV） was introduced to take road segment traffic surveillance. Considering the limited UAV maximum flight distance, UAV route planning problem was studied. First, a multi-objective optimization model of planning UAV route for road segment surveillance was proposed, which aimed to minimize UAV cruise distance and minimize the number of UAVs used. Then, an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV route planning problem. At last, a UAV flight experiment was conducted to test UAV route planning effect, and a case with three scenarios was studied to analyze the impact of different road segment lengths on UAV route planning. The case results show that the optimized cruise distance and the number of UAVs used decrease by an average of 38.43% and 33.33%, respectively. Additionally, shortening or extending the length of road segments has different impacts on UAV route planning.