Motion-dependent estimation of a spatial vector field with multiple vehicles
Motion-dependent estimation of a spatial vector field with multiple vehicles
复制标题
多车辆空间矢量场的运动相关估计
DOI：
10.1109/cdc.2018.8619696
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
H. Bai
中科院分区：
文献类型：
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作者：
H. Bai
我们考虑一个空间向量场估计问题的车辆建模为单轮车。矢量场被假定为以加性方式影响车辆的运动。我们调查的位置信息的车辆是否可以用来同时估计未知的字段参数和航向信息的车辆。从一个单一的车辆的情况下，我们设计了一个稳定的非线性观测器，并揭示了持续激励（PE）条件下的车辆的运动，保证收敛的场参数估计和航向估计几乎全球。接下来，我们扩展了多个车辆的观察员与强连接的通信拓扑结构，并提供了一个PE条件，以确保过滤器收敛。所设计的观察员的有效性证明与车辆估计旋转场的模拟。
We consider a spatial vector field estimation problem with vehicles modeled as unicycles. The vector field is assumed to affect the motion of the vehicles in an additive fashion. We investigate whether the position information of the vehicles can be used to simultaneously estimate the unknown field parameters and the heading information of the vehicles. Starting with a single vehicle case, we design a stable nonlinear observer and reveal a persistence of excitation (PE) condition on the vehicle's motion that guarantees the convergence of the field parameter estimates and the heading estimates almost globally. We next extend the observer for multiple vehicles with a strongly connected communication topology and provide a PE condition to ensure filter convergence. The effectiveness of the designed observers is demonstrated with simulations of vehicles estimating a rotational field.