当前位置: X-MOL 学术J. Syst. Eng. Electron. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
TDOA and track optimization of UAV swarm based on D-optimality
Journal of Systems Engineering and Electronics ( IF 1.9 ) Pub Date : 2021-01-06 , DOI: 10.23919/jsee.2020.000086
Zhou Ronghua , Sun Hemin , Li Hao , Luo Weilin

To solve the problem of time difference of arrival (TDOA) positioning and tracking of targets by the unmanned aerial vehicles (UAV) swarm in future air combat, this paper adopts the TDOA positioning method and uses time difference sensors of the UAV swarm to locate target radiation sources. Firstly, a TDOA model for the target is set up for the UAV swarm under the condition that the error variance varies with the received signal-to-noise ratio. The accuracy of the positioning error is analyzed by geometric dilution of precision (GDOP). The D-optimality criterion of the positioning model is theoretically derived. The target is positioned and settled, and the maximum value of the Fisher information matrix determinant is used as the optimization objective function to optimize the track of the UAV in real time. Simulation results show that the track optimization improves the positioning accuracy and stability of the UAV swarm to the target.

中文翻译:

基于D最优性的无人机群的TDOA和航迹优化

为解决无人机在未来空战中到达目标时差(TDOA)定位和目标跟踪的问题,本文采用TDOA定位方法,并利用无人机时差传感器对目标进行定位。辐射源。首先,在误差方差随接收信噪比变化的条件下,为无人机群建立目标的TDOA模型。定位误差的精度通过精度的几何稀释(GDOP)进行分析。从理论上推导了定位模型的D最优准则。定位并确定目标,并将Fisher信息矩阵行列式的最大值用作优化目标函数,以实时优化无人机的航迹。
更新日期:2021-01-08
down
wechat
bug