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近几年来 ,小波理论和信号的多尺度表示方法都得到了迅速发展 ,并在包括信号处理和图像处理在内的众多领域中得到了成功的应用 ,而在这些领域中 ,目前一个较为活跃的分支是基于小波变换的多尺度表示的统计信号处理 .运用多尺度分析的思想 ,将基于模型的动态系统分析方法与基于统计特性的多尺度信号变换方法相结合 ,建立起目标状态基于多源观测信息的多尺度分布式融合估计和单源观测信息的多尺度分布式估计两种新算法 ,用计算机仿真研究验证了算法效能 .
In recent years, wavelet theory and multi-scale representation of signals have been rapidly developed and successfully applied in many fields including signal processing and image processing. In these fields, one of the most active The branch is the statistical signal processing of multi-scale representation based on wavelet transform.Using the idea of multi-scale analysis, the model-based dynamic system analysis method is combined with the multi-scale signal transformation method based on statistical properties to establish the target state based on multi-source observation Two new algorithms of multi-scale distributed fusion estimation of information and multi-scale distributed estimation of single-source observational information are used to verify the effectiveness of the algorithm by computer simulation.