通信受限下网络化多传感器系统的Kalman融合估计

研究了一类通信受限下网络化多传感器系统的 Kalman 融合估计问题, 其中通信受限 是指系统在一个采样周期内只允许有限个传感器与融合中心通信. 首先, 提出了一种周期性分组传输的通信策略, 并将每组传感器所对应的局部估计系统描述成一个离散周期子系统模型. 其次, 每个子系统根据最新测量信息的更新时刻, 选择相应的 Kalman 估计器 (滤波器或预报器), 从而得到各子系统在每一时刻的一个局部最优估计, 再通过矩阵加权线性最小方差最优融合准则得到最优融合估计,并给出了Kalman融合估计器的设计方法. 最后, 通过一个目标跟踪例子验证所提方法的有效性.

Kalman Fusion Estimation for Networked Multi-sensor Fusion Systems with Communication Constraints

This paper investigates the fusion estimation problem for networked multi-sensor fusion systems with communication constraints that only finite sensors are allowed to communicate with the fusion center (FC). A novel periodic transmission strategy is proposed and each local estimation system is modeled as a discrete periodic subsystem. According to the latest measurement information update time, each subsystem chooses the appropriate Kalman estimator (filter or predictor) and obtains the local optimal estimate. Then an optimal fusion estimate is derived from the optimal fusion criterion weighted by matrices and a fusion Kalman estimator is derived. Finally, a target tracking example is given to show the effectiveness of the proposed method.