Method and device for tracking the path of motion of a moving object as well as computer program and data storage media

摘要

Method, device, computer program and computer program product for tracking the path of motion of a moving object. The method includes a) providing data of at least one state variable to be determined, which influences the movement of the moving object, at a first point in time; b) initializing the probability density (p) of the at least one state variable to be determined at the first point in time; c) predicting of the probability density (p) of the at least one state variable to be determined at a next point in time after the first point in time; d) verifying of whether measurement data are available that can be used for a calculation of the probability density (p) of the at least one state variable to be determined, and d′) recalculating the probability density (p) with these measurement data when such data is available; e) calculating the prediction values of the state variable(s) to be determined from the probability density (p); f) outputting the calculated prediction values to a downstream data processing device; and g) repeating the steps c) through f). The steps of initializing the probability density (p) of step b); predicting the probability density (p) of step c); recalculating the probability density (p) of step d′); and calculating the prediction values of step e) are performed by discretizing the probability density (p) on sparse grids.

主权项

1. A method for tracking the path of motion of a moving object having a position, speed vector, ballistic coefficient or other state variable that defines a current property of the motion of the moving object, comprising:
a) providing data of at least one state variable to be determined, which influences the movement of the moving object, at a first point in time; b) initializing the probability density (p) of the at least one state variable to be determined at the first point in time; c) predicting the probability density (p) of the at least one state variable to be determined at a next point in time after the first point in time; d) verifying whether measurement data are available for calculation of the probability density (p) of the at least one state variable to be determined; d′) recalculating the probability density (p) with these measurement data when such data is available; e) calculating the prediction values of the state variable(s) to be determined from the probability density (p); f) outputting the calculated prediction values to a downstream data processing device to determine at least one future location based on the calculated prediction values; and g) repeating the steps c) through f), wherein the:
initializing of the probability density (p) of step b);predicting of the probability density (p) of step c),recalculating of the probability density (p) of step d′); andcalculating of the prediction values of step e) are performed by discretizing the probability density (p) on sparse grids.