This paper studies the problem of bearing-based network localization, which aims to estimate the absolute positions of the nodes in a network by using the inter-node bearings measured in each node's local reference frame and the absolute positions of a small number of nodes called anchors. In the first part of the paper, we propose a continuous-time localization algorithm, which consists of coupled orientation and position estimation procedures. Compared to the existing works, the proposed algorithm has a concise form and guarantees global estimation convergence. In the second part of the paper, we study the discrete-time case which is still an open problem till now. We fill this gap by proposing a discrete-time localization algorithm to globally localize three-dimensional networks using locally measured bearings. The discrete-time algorithm does not require designing sufficiently small step sizes to ensure convergence. Numerical simulation is presented to verify the proposed algorithms.

中文翻译：

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使用局部测量的方位角进行全球收敛的分布式网络本地化

本文研究基于方位的网络本地化问题，该问题旨在通过使用在每个节点的本地参考框架中测量的节点间方位和少数几个称为“节点”的绝对位置来估计网络中节点的绝对位置。锚点。在本文的第一部分，我们提出了一种连续时间定位算法，该算法由耦合的方向和位置估计程序组成。与现有工作相比，该算法具有简洁的形式，并保证了全局估计的收敛性。在本文的第二部分中，我们研究了离散时间情况，到目前为止，这仍然是一个尚待解决的问题。我们通过提出一种离散时间定位算法来弥补这一空白，该算法使用局部测量的轴承对三维网络进行全局定位。离散时间算法不需要设计足够小的步长即可确保收敛。通过数值仿真验证了所提出的算法。