Convergence analysis of state estimation for UAV formation under GPS‐denied environments

Yu Ding, Zhengye Wang, Yirui Cong, Xiangke Wang
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Abstract

In this article, we focus on the state estimation and formation control problem for a multi‐UAV system, where only parts of UAVs have GPS measurements, that is, the anchors, and the other UAVs measure their relative positions with anchors. With a second‐order discrete‐time model of each UAV in the formation, we analyze the convergence of state estimation (including its expectation and covariance) for commonly used consensus‐based formation control protocols, under the effect of control and measurement noise. More specifically, based on the discrete‐time stability analysis, we obtain the sufficient and necessary conditions for the expectation stability of the formation control. Using the fixed point theorem in positive symmetric matrix subspace and observability analysis, we rigorously prove that the covariance of estimation is bounded if and only if the anchor node set is globally reachable. Based on our analysis, the formation control parameters and system topology can be designed to satisfy sufficient conditions, such that the desired formation pattern can be achieved for the multi‐UAV dynamic system under GPS‐denied environments. Simulation results corroborate the effectiveness of our theoretical results.
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全球定位系统失效环境下无人机编队状态估计的收敛性分析
在本文中,我们将重点研究多无人机系统的状态估计和编队控制问题,在该系统中,只有部分无人机(即锚机)拥有 GPS 测量数据,其他无人机通过锚机测量其相对位置。利用编队中每架无人机的二阶离散时间模型,我们分析了在控制和测量噪声影响下,常用的基于共识的编队控制协议的状态估计收敛性(包括其期望和协方差)。更具体地说,基于离散时间稳定性分析,我们得到了编队控制期望稳定性的充分和必要条件。利用正对称矩阵子空间中的定点定理和可观测性分析,我们严格证明了当且仅当锚节点集是全局可达时,估计的协方差是有界的。基于我们的分析,编队控制参数和系统拓扑结构的设计可以满足充分条件,从而使多无人飞行器动态系统在 GPS 信号缺失的环境下实现理想的编队模式。仿真结果证实了我们理论结果的有效性。
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