What the collapse of the ensemble Kalman filter tells us about particle filters
What the collapse of the ensemble Kalman filter tells us about particle filters
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DOI：
10.1080/16000870.2017.1283809
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发表时间：
2017-01-01
影响因子：
2
通讯作者：
Snyder, Chris
中科院分区：
文献类型：
--
作者：
Morzfeld, Matthias;Hodyss, Daniel;Snyder, Chris
集合卡尔曼滤波（EnKF）是解决高维气象问题的一种可靠的资料同化工具。另一方面，EnKF可以被解释为粒子滤波器，粒子滤波器（PF）在高维问题中崩溃。我们解释说，这些看似矛盾的陈述提供了有关PF功能在某些高维问题的见解，特别是支持最近的努力在气象学“本地化”粒子滤波器，即限制其附近的观察的影响。
The ensemble Kalman filter (EnKF) is a reliable data assimilation tool for high-dimensional meteorological problems. On the other hand, the EnKF can be interpreted as a particle filter, and particle filters (PF) collapse in high-dimensional problems. We explain that these seemingly contradictory statements offer insights about how PF function in certain high-dimensional problems, and in particular support recent efforts in meteorology to 'localize' particle filters, i.e. to restrict the influence of an observation to its neighbourhood.