This invention relates to the field of intelligent transportation and vehicle-to-everything (V2X)
data processing technology, and discloses a method and
system for evaluating the
layout of V2X meteorological observation based on
data assimilation. The key technical points are: a data cleaning module acquires multi-source hardware
sensing data and performs physical interference stripping based on a nonlinear compensation model; a
spatial mapping module constructs spatial
Gaussian attenuation weights and performs
coordinate mapping from discrete point trajectories to a static topological grid; a
simulation error module schedules the hardware accelerator to run the
simulation environment and deduces the dynamic observation error
covariance based on an LSTM network; an assimilation evaluation module first applies the consistent Kalman filtering mechanism to perform physical state assimilation of the meteorological background field and sensor data, then quantifies the
information gain scalar of the virtual deployment nodes, and finally configures a multi-objective constraint cost function to solve for the optimal sensor network hardware topology scheme; and an instruction execution module extracts local meteorological slices coupled with
traffic flow features, generates physical prevention and control early warning instructions, and issues them for execution.