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针对多传感器观测环境下带乘性噪声系统的逆向最优滤波与反褶积融合估计问题 ,本文提出了 1种基于极大似然准则的最优融合算法。该算法中各单传感器间并行计算 ,并且融合中心与单传感器处理中心间无反向通讯 ,因而执行效率较高。仿真表明 ,该融合算法产生的逆向滤波与反褶积比单传感器处理结果有较明显提高
In order to solve the problem of optimally filtering and deconvolution estimation of the system with multiplicative noise in a multisensor observation environment, an optimal fusion algorithm based on the maximum likelihood criterion is proposed in this paper. In this algorithm, each single sensor is calculated in parallel, and there is no reverse communication between fusion center and single sensor processing center, so the execution efficiency is higher. The simulation results show that the inverse filtering and deconvolution generated by the fusion algorithm have more obvious improvement than single sensor processing