Relative navigation method for unmanned aerial vehicles formation using consensus unscented Kalman filter

Zhixing Zhuang, Baichun Gong, Xiucai Ding, Mingrui Hao, Linxiu Chen
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Abstract

A relative navigation method in which the measurement information between aircraft only has distance or angle was proposed to achieve accurate relative navigation between aircraft formations in the global navigation satellite system (GNSS) Denied Environment. In addition, four relative measurement schemes are analyzed. An augmented state is introduced in the relative navigation system model, and the observability analysis of the navigation system is carried out relying on the Lie derivative theory, which gives the limitation of motion: the relative position and velocity of the aircraft cannot be parallel or zero, and a single aircraft cannot keep flying straight. A consensus unscented Kalman filter (CUKF) algorithm is established using the geometric characteristics in flight. The observability of the system state is improved after using the additional constraint. Finally, a standard Monte Carlo simulation system is established, and the system simulation is carried out, which shows that the Observability analysis is verified to be correct, and the algorithm demonstrates high accuracy.
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基于一致无嗅卡尔曼滤波的无人机编队相对导航方法
为了在全球导航卫星系统(GNSS)拒绝环境下实现飞机编队之间的精确相对导航,提出了一种飞机间测量信息只有距离或角度的相对导航方法。此外,还分析了四种相关的测量方案。在相对导航系统模型中引入增广状态,利用李氏导数理论对导航系统进行可观测性分析,给出了运动的局限性:飞行器的相对位置和速度不能为平行或为零,单个飞行器不能保持直线飞行。利用飞行中的几何特征,建立了一致无气味卡尔曼滤波(CUKF)算法。引入附加约束后,系统状态的可观察性得到了提高。最后,建立了标准蒙特卡罗仿真系统,并进行了系统仿真,验证了可观察性分析的正确性,算法具有较高的精度。
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