无人机遂行编队飞行中的纯方位无源定位  

Pure Azimuth Passive Positioning in Formation Flight of UAVs

作　　者：仵云凡 朱代根[1] 高朋 艾慧婷 李娟[1] Wu Yunfan;Zhu Daigen;Gao Peng;Ai Huiting;Li Juan

机构地区：[1]西南林业大学机械与交通学院,云南省昆明市650224

出　　处：《时代汽车》2023年第6期25-28,共4页Auto Time

摘　　要：无人机集群在遂行编队飞行时,为避免外界干扰,应尽可能保持电磁静默,少向外发射电磁波信号。为保持编队队形,拟采用纯方位无源定位的方法调整无人机的位置。基于此,建模旨在研究无人机遂行编队飞行中的纯方位无源定位问题。本文针对静止辐射源与移动辐射源分别提出到达时间差/到达角度定位(TDOA/AOA)和到达时间差/到达频率(TDOA/FDOA)联合定位方法,在此基础上推导了无源定位算法的静止/移动辐射源状态矢量的克拉美罗下界,为分析无源定位精度提供一个定量标准,建立了被动接收信号无人机的定位模型。接着,建立一种结合非线性滤波算法改善定位性能的模型,最终计算可得还需要3架无人机发射信号,才能实现无人机的有效定位。最后,本文对算法有效性进行了验证。When the UAV swarm is flying in formation,in order to avoid external interference,it should maintain electromagnetic silence as much as possible and emit less electromagnetic wave signals outward.In order to maintain the formation,it is proposed to adjust the position of the UAV by using the method of pure azimuth passive positioning.Based on this,the modeling aims to study the pure azimuth passive positioning problem in the flight of UAV formation.In this paper,the joint localization methods of arrival time diference/arrival angle localization(TDOA/AOA)and arrival time diference/arrival frequency(TDOA/FDOA)are proposed for static and moving radiation sources,respectively,and on this basis,the Kramero lower bound of the state vector of the stationary/moving radiator of the passive positioning algorithm is derived,which provides a quantitative standard for analyzing the passive positioning accuracy,and establishes the positioning model of passive receiving signal UAV.Then,a model combined with nonlinear filtering algorithm is established to improve the positioning performance,and finally it is calculated that three UAVs need to transmit signals to achieve efective positioning of UAVs.Finally,this paper verifies the algorithm efectiveness.

关 键 词：无人机 纯方位无源定位 非线性滤波算法 优化算法 

分 类 号：TN9[电子电信—信息与通信工程]