摘要
对带观测滞后和有色观测噪声的多传感器自回归滑动平均(ARMA)信号,提出一种反卷积加权融合Kalman滤波方法,其特点是将信号滤波问题转换为反卷积估计问题,并将观测滞后嵌入到反卷积模型中。仿真例子说明,按标量加权融合算法的精度高于每个局部滤波器的精度,说明了算法的有效性。
For multi-sensor ARMA signal with the measurement delays and colored noises, a deconvolution weighted fusion Kalman filtering method is presented where the signal filtering problem is converted into a deconvolution esti- mation problem and the measurement delays are embedded into the deconvolution model. Simulation example illus- trates that the accuracy of the fused algorithm weighted sensor by scalars is higher than that of each local filter. A simple example shows its effectiveness.
出处
《黑龙江大学自然科学学报》
CAS
北大核心
2013年第4期458-461,共4页
Journal of Natural Science of Heilongjiang University
基金
国家自然科学基金资助项目(60874063)
