针对在WiFi环境下使用TDOA(Time Difference of Arrival)和AOA(Time of Arrival)算法对移动终端进定位时需要添加额外硬件且定位精度不够高的问题,提出了一种TDOAAOE混合定位算法。该方法不使用信号到达角而使用信号发出角AOE(Angle of ...针对在WiFi环境下使用TDOA(Time Difference of Arrival)和AOA(Time of Arrival)算法对移动终端进定位时需要添加额外硬件且定位精度不够高的问题,提出了一种TDOAAOE混合定位算法。该方法不使用信号到达角而使用信号发出角AOE(Angle of Emission,AOE)信息进行定位,通过电机带动有向天线旋转,并将有向天线的角度信息编码到信标中,移动终端获取信标后解码即可完成定位,以此代替了测量信号角度的传感器。同时,该方法将TDOA时间差的思想融合到了AOE测量中,减小了角度测量误差。实验结果表明,TDOAAOE混合定位算法与TDOA、AOA算法相比,具有更好的定位性能。展开更多
Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system comp...Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment uncertainty.To address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network.In the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-Network for mission planning.Then,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts.The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning.The simulation proves the effectiveness of this approach.展开更多
文摘针对在WiFi环境下使用TDOA(Time Difference of Arrival)和AOA(Time of Arrival)算法对移动终端进定位时需要添加额外硬件且定位精度不够高的问题,提出了一种TDOAAOE混合定位算法。该方法不使用信号到达角而使用信号发出角AOE(Angle of Emission,AOE)信息进行定位,通过电机带动有向天线旋转,并将有向天线的角度信息编码到信标中,移动终端获取信标后解码即可完成定位,以此代替了测量信号角度的传感器。同时,该方法将TDOA时间差的思想融合到了AOE测量中,减小了角度测量误差。实验结果表明,TDOAAOE混合定位算法与TDOA、AOA算法相比,具有更好的定位性能。
基金Projects(61071096,61003233,61073103)supported by the National Natural Science Foundation of ChinaProjects(20100162110012,20110162110042)supported by the Research Fund for the Doctoral Program of Higher Education of China
文摘Mission planning was thoroughly studied in the areas of multiple intelligent agent systems,such as multiple unmanned air vehicles,and multiple processor systems.However,it still faces challenges due to the system complexity,the execution order constraints,and the dynamic environment uncertainty.To address it,a coordinated dynamic mission planning scheme is proposed utilizing the method of the weighted AND/OR tree and the AOE-Network.In the scheme,the mission is decomposed into a time-constraint weighted AND/OR tree,which is converted into an AOE-Network for mission planning.Then,a dynamic planning algorithm is designed which uses task subcontracting and dynamic re-decomposition to coordinate conflicts.The scheme can reduce the task complexity and its execution time by implementing real-time dynamic re-planning.The simulation proves the effectiveness of this approach.
