 A Novel Bayesian Method for Calculating Circular Error Probability with Systematic-Biased Prior InformationBowen Liu, Xiaojun Duan and Liang Yan Mathematical Problems in Engineering, 2018, vol. 2018, 1-9 Abstract: Circular Error Probability (CEP) is defined as the radius of a circle where the probability of an impact point being inside is 50%, which is also widely used as a measure of the guidance weapon systems’ precision. In order to achieve a fusion of various test information, Bayesian methods and improved Bayesian methods have been extensively studied in calculating the CEP. Nevertheless, these methods could fail when there exists unknown systematic bias in the prior information. Therefore, a novel method called Bayesian estimation based on representative points (BERP) with an optimization procedure for determining the optimal number of representative points is proposed in this paper. Explicit theoretical analyses demonstrate that the BERP outperforms the classical Bayesian methods when fusing the slightly biased prior information and also give the bound of the systematic bias for stopping using the heavily biased prior information. Moreover, when the systematic bias is within the bound, simulation results indicate that our method is credible and outperforms the classical Bayesian method in calculating the CEP of guidance weapon systems. Date: 2018 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:5930109 DOI: 10.1155/2018/5930109 Access Statistics for this article More articles in Mathematical Problems in Engineering from Hindawi |
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