一种随机传感器增益退化下的多传感融合估计方法

A Multi-sensor Fusion Estimating Approach for Stochastic Sensor Gain Degradation

研究了传感器存在随机增益退化故障的不确定随机系统的融合状态估计问题。首先,将系统不确定性建模为系统矩阵中存在的随机参数扰动,利用期望与方差已知的随机变量描述传感器随机增益退化故障。然后,设计了一种局部估计器,并以估计器的增益为决策量,建立以矩阵加权融合估计误差为代价的优化问题。对于获得最优的决策增益的闭合形式是非常困难的,所以,选取融合估计误差的一个上界并对其进行最小化处理,得到次优的决策增益。最后,给出算例仿真来验证有效性。

The multi-sensor fusion estimation problem is investigated in the paper for a class of uncertain systems with stochastic sensor gain degradation. Firstly, the model＇s uncertainty is described by stochastic parameter perturbations considered in the system matrix. The sensor gain degradation is described by a random variable whose expectation and variance are assumed to be known. Then, a kind of local unbiased estimator is proposed, and an optimization problem is established by taking the matrix weighted fusion estimation error as the Cost function, and the local filter gains as the decision variables. Considering that obtaining the closed form of the optimal consensus filter gains is a challenging problem, a set of sub-optimal local filter gains are computed based on minimizing an upper bound of the cost function. Finally, a simulation example is given to confirm the effectiveness of the proposed approach.