配置MIMU(Micro Inertial Measurement Unit,微惯性测量单元)中的加速度计工作在倾角仪状态,利用当地的重力加速度计算MAV(Micro Air Vehicles,微小型飞行器)的姿态角。同时利用MIMU中的陀螺仪,计算载体的姿态角。提出了一种构造加权系...配置MIMU(Micro Inertial Measurement Unit,微惯性测量单元)中的加速度计工作在倾角仪状态,利用当地的重力加速度计算MAV(Micro Air Vehicles,微小型飞行器)的姿态角。同时利用MIMU中的陀螺仪,计算载体的姿态角。提出了一种构造加权系数的方法,可以根据MIMU的特性,构造不同性能的加权系数。通过对姿态角进行加权平均,实现惯性数据的融合,对MAV的姿态进行估计。该方法既保证了飞行器稳定飞行时姿态估计的精度,避免了姿态误差随时间的积累;又保证了姿态估计系统的动态性能,减小了系统的动态误差。基于该方法搭建的微小型AHRS(Attitude and Heading Reference System,姿态航向参考系统)体积小、重量轻、精度高,特别适用于载荷与体积都有限的载体使用。展开更多
The formation of the manned aerial vehicle/unmanned aerial vehicle(MAV/UAV) task coalition is considered. To reduce the scale of the problem, the formation progress is divided into three phases. For the task clusterin...The formation of the manned aerial vehicle/unmanned aerial vehicle(MAV/UAV) task coalition is considered. To reduce the scale of the problem, the formation progress is divided into three phases. For the task clustering phase, the geographical position of tasks is taken into consideration and a cluster method is proposed. For the UAV allocation phase, the UAV requirement for both constrained and unconstrained resources is introduced, and a multi-objective optimal algorithm is proposed to solve the allocation problem. For the MAV allocation phase, the optimal model is firstly constructed and it is decomposed according to the ideal of greed to reduce the time complexity of the algorithm. Based on the above phases, the MAV/UAV task coalition formation method is proposed and the effectiveness and practicability are demonstrated by simulation examples.展开更多
A formation model of manned/unmanned aerial vehicle(MAV/UAV) collaborative combat can qualitatively and quantitatively analyze the synergistic effects.However,there is currently no effective and appropriate model cons...A formation model of manned/unmanned aerial vehicle(MAV/UAV) collaborative combat can qualitatively and quantitatively analyze the synergistic effects.However,there is currently no effective and appropriate model construction method or theory,and research in the field of collaborative capability evaluation is basically nonexistent.According to the actual conditions of cooperative operations,a new MAV/UAV collaborative combat network model construction method based on a complex network is presented.By analyzing the characteristic parameters of the abstract network,the index system and complex network are combined.Then,a method for evaluating the synergistic effect of the cooperative combat network is developed.This method provides assistance for the verification and evaluation of MAV/UAV collaborative combat.展开更多
文摘配置MIMU(Micro Inertial Measurement Unit,微惯性测量单元)中的加速度计工作在倾角仪状态,利用当地的重力加速度计算MAV(Micro Air Vehicles,微小型飞行器)的姿态角。同时利用MIMU中的陀螺仪,计算载体的姿态角。提出了一种构造加权系数的方法,可以根据MIMU的特性,构造不同性能的加权系数。通过对姿态角进行加权平均,实现惯性数据的融合,对MAV的姿态进行估计。该方法既保证了飞行器稳定飞行时姿态估计的精度,避免了姿态误差随时间的积累;又保证了姿态估计系统的动态性能,减小了系统的动态误差。基于该方法搭建的微小型AHRS(Attitude and Heading Reference System,姿态航向参考系统)体积小、重量轻、精度高,特别适用于载荷与体积都有限的载体使用。
基金supported by the National Natural Science Foundation of China(61573017 61703425)the Aeronautical Science Fund(20175796014)
文摘The formation of the manned aerial vehicle/unmanned aerial vehicle(MAV/UAV) task coalition is considered. To reduce the scale of the problem, the formation progress is divided into three phases. For the task clustering phase, the geographical position of tasks is taken into consideration and a cluster method is proposed. For the UAV allocation phase, the UAV requirement for both constrained and unconstrained resources is introduced, and a multi-objective optimal algorithm is proposed to solve the allocation problem. For the MAV allocation phase, the optimal model is firstly constructed and it is decomposed according to the ideal of greed to reduce the time complexity of the algorithm. Based on the above phases, the MAV/UAV task coalition formation method is proposed and the effectiveness and practicability are demonstrated by simulation examples.
文摘A formation model of manned/unmanned aerial vehicle(MAV/UAV) collaborative combat can qualitatively and quantitatively analyze the synergistic effects.However,there is currently no effective and appropriate model construction method or theory,and research in the field of collaborative capability evaluation is basically nonexistent.According to the actual conditions of cooperative operations,a new MAV/UAV collaborative combat network model construction method based on a complex network is presented.By analyzing the characteristic parameters of the abstract network,the index system and complex network are combined.Then,a method for evaluating the synergistic effect of the cooperative combat network is developed.This method provides assistance for the verification and evaluation of MAV/UAV collaborative combat.
