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Research on aiming methods for small sample size shooting tests of two-dimensional trajectory correction fuse 被引量:1
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作者 Chen Liang Qiang Shen +4 位作者 Zilong Deng Hongyun Li Wenyang Pu Lingyun Tian Ziyang Lin 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第3期506-517,共12页
The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction ... The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction fuse actuator.The impact point easily deviates from the target,and thus the correction result cannot be readily evaluated.However,the cost of shooting tests is considerably high to conduct many tests for data collection.To address this issue,this study proposes an aiming method for shooting tests based on small sample size.The proposed method uses the Bootstrap method to expand the test data;repeatedly iterates and corrects the position of the simulated theoretical impact points through an improved compatibility test method;and dynamically adjusts the weight of the prior distribution of simulation results based on Kullback-Leibler divergence,which to some extent avoids the real data being"submerged"by the simulation data and achieves the fusion Bayesian estimation of the dispersion center.The experimental results show that when the simulation accuracy is sufficiently high,the proposed method yields a smaller mean-square deviation in estimating the dispersion center and higher shooting accuracy than those of the three comparison methods,which is more conducive to reflecting the effect of the control algorithm and facilitating test personnel to iterate their proposed structures and algorithms.;in addition,this study provides a knowledge base for further comprehensive studies in the future. 展开更多
关键词 Two-dimensional trajectory correction fuse Small sample size test Compatibility test KL divergence Fusion bayesian estimation
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Determ ination of Even Degree of Animal Population
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作者 Song Ren xue,Yang Yun qing ( Northeast Agricultural University, Harbin 150030 PRC) 《Journal of Northeast Agricultural University(English Edition)》 CAS 1999年第2期158-160,共3页
The even degree of animal population is generlay measured by the coefficient of variation of major economic characters.Facing the coefficient of variation,a statistic with complex properties,we achieved indirectly the... The even degree of animal population is generlay measured by the coefficient of variation of major economic characters.Facing the coefficient of variation,a statistic with complex properties,we achieved indirectly the determination of confidence interval for even degree of an animal population by analysing the reciprocal of the statistic.The sample size which is suitable to the determination of the even degree of an animal population was probed into within the extent of permissive estimation error. 展开更多
关键词 even degree coefficient of variation DETERMINATION sample size
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