基于一致性校验的贝叶斯估计器性能评估  

Performance Evaluation of Bayesian Estimator with Consistency Validation

作　　者：孙作雷[1] 李影[1] 张波[2] 张文[1] 

机构地区：[1]上海海事大学信息工程学院,上海201306 [2]中国科学院上海高等研究所,上海201210

出　　处：《系统仿真学报》2016年第3期569-576,共8页Journal of System Simulation

基　　金：国家自然科学基金项目(61105097;51279098;61401270);上海海事大学研究生创新基金(2015ycx059)

摘　　要：针对贝叶斯估计器设计中缺乏严谨评估手段的问题,提出以估计一致性作为表征贝叶斯估计器性能的核心指标。通过分析观测更新中新息序列的无偏性和白特性,构造正则化新息平方序列,并对它实施卡方校验以判断相应贝叶斯估计器后验概率的估计一致性。仿真结果表明所提算法能同时在线性及非线性系统中有效辨识贝叶斯估计器设计中不恰当的参数配置,进而评估估计器性能。Considering the lack of sound evaluation method for Bayesian estimator design, an approach employing consistency as the core criterion was proposed. By studying the unbiasedness and whiteness of innovation sequence yielded during observation update routine, the normalized innovations square （NIS） was constructed, and then the chi-square test being able to detect the Posterior＇s consistency was carried out on NIS. Experiments demonstrate that the proposed algorithm can identify the inappropriate parameter configuration for both linear and nonlinear systems, therefore the performance of the estimators can be evaluated.

关 键 词：贝叶斯估计器 一致性 卡方检测 正则化新息平方 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]