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Fixed-lag alpha-beta filter for target trajectory smoothing

机译:固定滞后的alpha-beta滤波器用于目标轨迹平滑

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A fixed-lag Kalman smoother can be used for target trajectory reconstruction in postmission data analysis from noisy sensor data, where lag is the time difference between the time of the latest available measurement (or the latest measurement used for estimation) and the time of the smoothed estimate. Based on the steady-state conditions of a Kalman smoother, a recursive method for calculating the steady-state gains and covariance matrix of a fixed-lag alpha-beta smoother is derived and presented. The equations derived for the alpha-beta fixed-lag smoother were verified using a Kalman smoother in steady-state, and the results are used to characterize the benefits achieved with fixed-lag smoothing.
机译:固定滞后Kalman平滑器可用于从嘈杂的传感器数据进行的后发射数据分析中的目标轨迹重建,其中滞后是最新可用测量时间(或用于估计的最新测量)与测量时间之间的时间差。平滑估计。基于卡尔曼平滑器的稳态条件,推导并提出了一种计算固定滞后α-β平滑器的稳态增益和协方差矩阵的递归方法。使用卡尔曼平滑器在稳态下验证了针对α-β固定滞后平滑器的方程,并将结果用于表征使用固定滞后平滑所实现的好处。

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