非平稳随机序列的自适应加权融合算法

Adaptive weighted fusion algorithm for non-stationary random sequence

针对非平稳的多传感器测量信号的融合问题,提出了一种非平稳随机序列的自适应加权融合算法,它能够实时估计并自适应地在线调整各传感器的最优加权因子。仿真研究表明:该算法能够有效地减小融合估计值的方差,提高测量精度。

Aimed at the fusion problem of non-stationary signals measured by multi-sensor system, an adaptive weighted fusion algorithm for non-stationary random sequence is proposed, by which the optimum weighted factor of each sensor can be estimated and adaptively adjusted on-line. Simulation results demonstrate that the developed algorithm can efficiently decrease the variance of the fused value and improve measurement precision.