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Comparison of angle-only filtering algorithms in 3D using EKF, UKF, PF, PFF, and ensemble KF

机译:使用EKF,UKF,PF,PFF和集成KF在3D中仅角度滤波算法的比较

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In our previous work, we compared the performance of the extended Kalman filter (EKF), unscented Kalman filter (UKF), and particle filter (PF) for the angle-only filtering (AOF) problem in 3D using Cartesian coordinates and modified spherical coordinates (MSC) for the relative state vector. We found that the UKF-MSC and EKF-MSC had the best performance in accuracy, the UKF-MSC being slightly better than the EKF-MSC. The PF didn't perform well compared with the EKF and UKF and had a higher computational cost. In this work, we compare the performance of the particle flow filter (PFF) with the other filters for the AOF problem. In addition, we also analyze the performance of two versions of the ensemble Kalman filter (EnKF) in this comparative study. We present numerical results from Monte Carlo simulations to analyze the state estimation accuracy and computational cost of these filters.
机译:在我们之前的工作中,我们比较了使用笛卡尔坐标和修改后的球面坐标的扩展卡尔曼滤波器(EKF),无味卡尔曼滤波器(UKF)和粒子滤波器(PF)在3D中仅角度滤波(AOF)问题的性能(MSC)为相对状态向量。我们发现UKF-MSC和EKF-MSC在准确度方面具有最佳性能,UKF-MSC比EKF-MSC稍好。与EKF和UKF相比,PF性能不佳,并且具有较高的计算成本。在这项工作中,我们比较了粒子流过滤器(PFF)和其他过滤器在AOF问题上的性能。此外,在此比较研究中,我们还分析了两种版本的集成卡尔曼滤波器(EnKF)的性能。我们提出了蒙特卡洛模拟的数值结果,以分析这些滤波器的状态估计精度和计算成本。

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