The second fusion layer is used to determine the optimal scalar weighting coefficients, and obtain the optimal fusion Kalman multi-step predictor weighted by scalars. 第二融合层用来确定最优标量加权系数,进而获得标量加权最优融合Kalman多步预报器。
Based on this fusion algorithm, a scalar weighting multi-sensor optimal information fusion decentralized Kalman multi-step predictor with a fault tolerant property is given for the discrete linear stochastic system measured by multiple sensors. 基于该融合算法,对被多个传感器观测的离散线性随机系统,给出了具有容错性的多传感器标量加权最优信息融合分布式Kalman多步预报器。