Equal Weight Particle Filter Data Assimilation Based on Kalman Proposal Density

Ocean energy is inexhaustible clean energy. Ocean energy is diverse, mainly including wave energy, tidal energy, tidal energy and temperature difference energy. The use of marine energy for power generation can improve the energy structure and environment, and is conducive to the development of marine resources, which has attracted the attention of many countries. The study of Oceanography mainly relies on numerical simulation and direct ocean observation. The data assimilation method is an important means to effectively combine multi-source atmospheric and oceanic observations and numerical prediction models. Combining these two methods can better predict changes in the marine environment, which is beneficial to the development and utilization of ocean energy. In this paper, the equal weight particle filter data assimilation method is studied, and the dependence of traditional particle filter methods on future observations is analyzed. An equal weight particle filter assimilation method based on Kalman proposal density is given.