A low-altitude turbulence three-dimensional monitoring method based on multi-source data fusion

Abstract

This invention discloses a three-dimensional monitoring and forecasting method for low-altitude turbulence based on multi-source data fusion. Based on acquired wind profiler radar and microwave radiometer data, a first turbulence intensity calculation model and a second turbulence intensity calculation model are constructed respectively. The reliability of the second turbulence intensity calculation model is verified using the first turbulence intensity calculation model as a benchmark. Then, based on verified reliable regional multi-source observation data, the first and second turbulence intensity calculation models are executed in parallel to generate multiple preliminary three-dimensional turbulence intensity estimation fields. Finally, a Kalman filter assimilation system with the three-dimensional turbulence field as the state variable is constructed. Through an adaptive fusion mechanism that dynamically adjusts the observation weights of each algorithm, a high-confidence three-dimensional turbulence intensity analysis field is generated. This method solves the problems of lack of reliability verification for single-point inversion and difficulty in collaboratively constructing a three-dimensional turbulence field from multi-source data, achieving refined and three-dimensional monitoring and early warning of low-altitude turbulence.

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