针对无人机集群编队问题，提出一种无人机间相对定位方法。利用每架无人机上呈三角形配置的3个无线电收发装置，基于高精度载波相位测量技术，采用扩展卡尔曼滤波(extended Kalman filter，EKF)算法，实现对无人机位置、速度和姿态的同步求解；给出相对定位模型和具体的滤波实现算法，并对无人机集群在“线”“面”“体”等不同空间布局情况下的飞行状态进行估计和分析。结果表明：相比于“线”布局，“面”布局可显著提升定位性能，与“体”布局获得的效果无明显差异，说明在无人机集群定位系统中，合理配置观测几何能够有效提高相对定位精度；仿真算例表明，在良好观测几何的条件下，冗余观测数据可进一步提高系统稳定性。
Aiming at the formation problem of unmanned aerial vehicles (UAVs), a relative positioning method between UAVs is proposed. Based on the high precision carrier phase measurement technology and the extended Kalman filter (EKF) algorithm, the synchronous solution of the position, velocity and attitude of the UAV is realized by using three radio transceivers configured in a triangle on each UAV; The relative positioning model and the specific filtering algorithm are given, and the flight States of the UAV group in different spatial layouts such as line, “surface” and “body” are estimated and analyzed. The results show that compared with the “line” layout, the “surface” layout can significantly improve the positioning performance, and there is no significant difference with the “body” layout, which indicates that in the UAV group positioning system, the rational configuration of observation geometry can effectively improve the relative positioning accuracy. Simulation examples show that under the condition of good observation geometry, redundant observation data can further improve the system stability.