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Precession period estimation of ballistic target in midcourse

机译:中段弹道目标进动周期估计

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To solve the problem of inaccuracy and bad anti-noise performance in traditional methods on precession period estimation, a novel approach is suggested. The approach is based on the exploiting average magnitude difference function (AMDF) and autocorrelation function (ACF). No a priori information about ballistic target under classification is required for estimation of period. The trend term of AMDF is eliminated after empirical mode decomposition (EMD) processes. Then the ACF is used to weight the new AMDF. Thus the new feature is constructed to estimate precession period. Synthetic data of ballistic target is used both for performance evaluation of suggested and traditional approaches. The benefit of suggested approach comparing to traditional approaches is demonstrated using the mean square errors of precession period estimates computed in additive noise environment.
机译:针对旋进周期估计中传统方法不准确,抗噪性能差的问题,提出了一种新的方法。该方法基于利用平均幅度差函数(AMDF)和自相关函数(ACF)。估计期间不需要分类中的弹道目标的先验信息。在经验模式分解(EMD)过程之后,将消除AMDF的趋势项。然后,使用ACF加权新的AMDF。因此,构造新特征来估计进动时间。弹道目标的综合数据可用于建议方法和传统方法的性能评估。使用加性噪声环境中计算的进动周期估计值的均方误差,证明了与传统方法相比建议方法的优势。

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