摘要
该文将基于模型的动态分析方法与具有统计性的多尺度信号变换方法相结合,基于最细尺度上给定的状态模型和不同尺度上给出的多速率传感器动态系统,建立了一组新的多尺度动态模型和多尺度误差模型;利用确立的尺度之间的递归关系,给出了一种新的多尺度递归数据融合估计算法,在最细尺度上获得了状态基于全局信息的融合估计值;理论推理证明了这种方法的正确性,计算机仿真验证了算法的有效性。
By combining the model-based analysis method for dynamic systems with multi-scale signal transformation method based on statistical characteristics, this paper proposed a group of inultiscale dynamic models and multiscalc error models based on the dynamic systems which consist of a state model given at the finest scale and multisensor having different sample rates at different scales. A new multiscale recursive fusion estimation algorithm is put forward by use of the recursive relationship between scales. At the finest scale the optimal fusion estimates are obtained on the basis of global information. Finally the validity of the method is proved and the effectiveness of the new algorithm is illustrated by use of an example.
出处
《电子与信息学报》
EI
CSCD
北大核心
2003年第3期306-312,共7页
Journal of Electronics & Information Technology
基金
国家自然科学基金(No.60174011)
河南省高校杰出科研人才创新工程项目(2002KYCX007)
河南省杰出青年科学基金(No.0312001900)
