态势估计中一种基于最大后验概率估计的时间推理方法
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A Temporal Reasoning Method Based on the Maximum Posteriori Estimation in Situation Assessment
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    摘要:

    态势估计中统计时间推理在许多应用中非常重要。Kirillov 的基于极大似然估计(Maximum Likelihood Estimation, MLE) 的推理方法将未知时间变量看作常数, 忽略了它的先验信息, 估计方差较大。针对这一问题, 本文首先建立了已知时间信息和未知时间变量之间的关系模型, 这一模型可用来解释Kirillov 的方法; 然后在这一模型下, 将未知时间变量扩展为随机变量, 采用基于最大后验概率估计(Maximum a Posteriori Estimation, MAP) 的方法进行统计时间推理。对两种推理算法的性能进行了分析和比较, 发现在较宽的范围内, 基于MAP 的方法性能优于基于MLE 的方法。

    Abstract:

    Stochastic temporal reasoning in situation assessment (SA) is very important in many applications. The approach based on Maximun Likelihood Estimation (MLE) treats the unknown temporal variable as a constant, which doesn't use a priori information and generates a larger/estimate variance. In this paper, the relation model of known temporal information and unknown temporal variable has been established, which can also be used for MLE-based method. In the model, the reasoning algorithm about time instants has been derived from treating the unknown temporal variable as random variable and introducing MAP estimation into temporal reasoning. The performance analysis between MAP-based method and MLE-based method shows that under some conditions, the estimate variance of MAP-based method is lower than that of the MLE-based method, and we have given these conditions in experiments.

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姚春燕,郁文贤,庄钊文.态势估计中一种基于最大后验概率估计的时间推理方法[J].国防科技大学学报,1998,20(6):69-73.
Yao Chunyan, Yu Wenxian, Zhuang Zhaowen. A Temporal Reasoning Method Based on the Maximum Posteriori Estimation in Situation Assessment[J]. Journal of National University of Defense Technology,1998,20(6):69-73.

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  • 收稿日期:1998-04-08
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  • 在线发布日期: 2014-01-03
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