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Instantaneous spectrum estimation of earthquake ground motions based on unscented Kalman filter method

机译:基于无味卡尔曼滤波方法的地震地震动瞬时谱估计

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摘要

Representing earthquake ground motion as time varying ARMA model, the instantaneous spectrum can only be determined by the time varying coefficients of the corresponding ARMA model. In this paper, unscented Kalman filter is applied to estimate the time varying coefficients. The comparison between the estimation results of unscented Kalman filter and Kalman filter methods shows that unscented Kalman filter can more precisely represent the distribution of the spectral peaks in time-frequency plane than Kalman filter, and its time and frequency resolution is finer which ensures its better ability to track the local properties of earthquake ground motions and to identify the systems with nonlinearity or abruptness. Moreover, the estimation results of ARMA models with different orders indicate that the theoretical frequency resolving power ofARMA model which was usually ignored in former studies has great effect on the estimation precision of instantaneous spectrum and it should be taken as one of the key factors in order selection of ARMA model.
机译:将地震地面运动表示为时变ARMA模型,瞬时频谱只能由相应ARMA模型的时变系数确定。本文采用无味卡尔曼滤波器来估计时变系数。无味卡尔曼滤波器和卡尔曼滤波器方法的估计结果比较表明,无味卡尔曼滤波器比时频卡尔曼滤波器能更精确地表示时频平面中频谱峰值的分布,并且其时间和频率分辨率更好,从而确保了更好的性能。跟踪地震地面运动的局部特性并识别具有非线性或突变性的系统的能力。而且,不同阶次的ARMA模型的估计结果表明,以前研究中通常忽略的ARMA模型的理论频率分辨能力对瞬时频谱的估计精度有很大的影响,应将其作为阶次的关键因素之一。选择ARMA模型。

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