多数现象或过程具有Markov性,对在不同尺度上拥有对同一目标进行观测的多传感器系统,利用Markov过程的条件独立性,提出了不规则树的新概念,建立了动态过程基于不规则二阶树的多尺度表示方法,给出了确定多尺度模型中各种参数的具体步骤,并通过计算机仿真实验验证了所建立的动态过程基于不规则树的多尺度表示方法和多尺度模型的有效性与实用性.
For the multiple sensors system, in which the uniform target at the same period is observed by the sensors with different characters at multiple scales, the notion of irregular tree is put forward and the multiscale representation is developed by the irregular second tree for the dynamic processes, utilizing the Markov statistical characteristics in most phenomena or processes. In addition, the parameters of the corresponding multiscale model are derived. Simulation results demonstrate the validity and practicability of the irregularly modeling.