Study on the construction of a time-space four-dimensional combined imaging model and moving target location prediction model

HIGHLIGHTS

SUMMARY

Based on artificial neural_network technology to learn the object-image mapping As shown in target points velocities, fed trained relative rate distribution -1.51%~1.02%; the time error at a into speed 40 mm/s is corresponding neural_network model, can bebewell predicted forfor temporal and spatial locorresponding neural_network model, can well predicted temporal and spatial roughly distributed between -0.09 and 0.08, with a relative error rate distribution of calization. With the continuous development of artificial neural_networks, their related techniques have been applied to trajectory prediction. In some simple prediction tasks, the . . .

 



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