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Parameter Estimation for Censored Exponential Random Variables

机译:删除指数随机变量的参数估计

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Estimating the parameter of a Swerling target's radar cross section (RCS) is of interest as it may provide a discriminating feature to aid measurement-to-track association in multi-target tracking problems. Proper estimation of this statistic requires the appropriate characterization of the probability distribution function of the target's signal to noise ratio (SNR) and, in particular, compensating for censoring due to detection thresholding and saturation. In this paper, the maximum likelihood estimator for the upper and lower censored pdf of an exponential random variable is derived, and a method for solving the resulting equation is given. Two computationally simpler approximations are also proposed, and the performance of the standard exponential estimator is compared to the derived estimator and approximations.
机译:估计抖动目标的雷达横截面(RCS)的参数,因为它可以提供一个辨别特征,以帮助在多目标跟踪问题中辅助测量到轨道关联。对该统计数据的正确估计需要适当表征目标信号对噪声比(SNR)的概率分布函数,并且特别地,补偿由于检测阈值和饱和而导致的抗冲。在本文中,推导了指数随机变量的上噬官PDF的最大似然估计,并给出了解决所得方程的方法。还提出了两个计算方式近似,并且将标准指数估计器的性能与导出的估计器和近似进行比较。

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