AERIAL VEHICLE POSITION ESTIMATION SYSTEM AND AERIAL VEHICLE POSITION ESTIMATION METHOD

An aerial vehicle position estimation system estimates the current position of an aerial vehicle by executing a machine learning model N using time-series data related to the aerial vehicle flying in a predetermined flight route as an input value. The machine learning model N is composed of an input cross-attention layer C, a self-attention layer S, and an output cross-attention layer C, and has a function of using the time-series data as an input value as first array data D and reconstructing the first array data based on predetermined weighting coefficients to generate second array data D