초록 ▼

According to one embodiment, bias estimation and orbit determination include receiving measurements in real time. The measurements include radar measurements and radar array orientation measurements. The radar measurements are generated by a radar system and indicate the location of a target. The ra

According to one embodiment, bias estimation and orbit determination include receiving measurements in real time. The measurements include radar measurements and radar array orientation measurements. The radar measurements are generated by a radar system and indicate the location of a target. The radar array orientation measurements are generated by a navigation system and indicate the orientation of a radar array of the radar system. A state variable set is used. The state variable set includes measurement variables and dynamic bias variables. For example, a state variable set may include orbit position, orbit velocity, radar orientation, and radar measurement variables, which in turn may include dynamic bias variables such as orientation bias variables and measurement bias variables. A measurement variable is associated with a measurement, and a dynamic bias variable is associated with bias of a measurement. The following are performed for a number of iterations to yield state value sets for the state variable set: updating a state value set according to the measurements to yield an updated state value set; and predicting a next state value set in accordance with the updated state value set. An orbit path is of the target determined from the state value sets in real time.

대표청구항 ▼

1. A method comprising: receiving a plurality of measurements in real time, the measurements comprising a plurality of radar measurements and a plurality of radar array orientation measurements, the radar measurements generated by a radar system tracking a target, the radar measurements indicating a

1. A method comprising: receiving a plurality of measurements in real time, the measurements comprising a plurality of radar measurements and a plurality of radar array orientation measurements, the radar measurements generated by a radar system tracking a target, the radar measurements indicating a location of the target, the radar array orientation measurements generated by a navigation system of the radar system, the radar array orientation measurements indicating an orientation of a radar array of the radar system;performing the following for a number of iterations to yield a plurality of state value sets for a state variable set, the state variable set comprising one or more measurement variables and one or more dynamic bias variables, a measurement variable associated with a measurement, a dynamic bias variable associated with bias of a measurement: updating a state value set according to the measurements to yield an updated state value set; andpredicting a next state value set in accordance with the updated state value set; anddetermining an orbit path of the target from the state value sets in real time. 2. The method of claim 1, the one or more bias variables comprising: a plurality of orientation bias variables associated with bias of an radar array orientation measurement; anda plurality of measurement bias variables associated with bias of a radar measurement. 3. The method of claim 1: the updating the state value set further comprising: updating the state value set and a covariance, the covariance correlating the measurement variables and the dynamic bias variables; andthe predicting the next state value set further comprising: calculating the next state value set and a next covariance. 4. The method of claim 1, further comprising: collecting the radar measurements; andbatch filtering the radar measurements to generate an initial state value set. 5. The method of claim 1, the performing the following to yield the plurality of state value sets further comprising: calculating a measurement residual according to the radar measurements and the radar array orientation measurements. 6. The method of claim 1, the updating the state value set further comprising: updating the state value set using a covariance that correlates the dynamic bias variables. 7. The method of claim 1, the predicting the next state value set further comprising: predicting the next state value set using an orbital model configured to determine a next path point from a current path point. 8. A system comprising: a memory configured to store a plurality of measurements in real time, the measurements comprising a plurality of radar measurements and a plurality of radar array orientation measurements, the radar measurements generated by a radar system tracking a target, the radar measurements indicating a location of the target, the radar array orientation measurements generated by a navigation system of the radar system, the radar array orientation measurements indicating an orientation of a radar array of the radar system; anda processor coupled to the memory and configured to: perform the following for a number of iterations to yield a plurality of state value sets for a state variable set, the state variable set comprising one or more measurement variables and one or more dynamic bias variables, a measurement variable associated with a measurement, a dynamic bias variable associated with bias of a measurement: update a state value set according to the measurements to yield an updated state value set; andpredict a next state value set in accordance with the updated state value set; anddetermine an orbit path of the target from the state value sets in real time. 9. The system of claim 8, the one or more bias variables comprising: a plurality of orientation bias variables associated with bias of an radar array orientation measurement; anda plurality of measurement bias variables associated with bias of a radar measurement. 10. The system of claim 8, the processor configured to: update the state value set by: updating the state value set and a covariance, the covariance correlating the measurement variables and the dynamic bias variables; andpredict the next state value set by: calculating the next state value set and a next covariance. 11. The system of claim 8, the processor configured to: collect the radar measurements; andbatch filter the radar measurements to generate an initial state value set. 12. The system of claim 8, the processor configured to yield the plurality of state value sets by: calculating a measurement residual according to the radar measurements and the radar array orientation measurements. 13. The system of claim 8, the processor configured to update the state value set by: updating the state value set using a covariance that correlates the dynamic bias variables. 14. The system of claim 8, the processor configured to predict the next state value set by: predicting the next state value set using an orbital model configured to determine a next path point from a current path point. 15. A non-transitory computer readable medium storing computer code that instructs a computer to: receive a plurality of measurements in real time, the measurements comprising a plurality of radar measurements and a plurality of radar array orientation measurements, the radar measurements generated by a radar system tracking a target, the radar measurements indicating a location of the target, the radar array orientation measurements generated by a navigation system of the radar system, the radar array orientation measurements indicating an orientation of a radar array of the radar system; andperform the following for a number of iterations to yield a plurality of state value sets for a state variable set, the state variable set comprising one or more measurement variables and one or more dynamic bias variables, a measurement variable associated with a measurement, a dynamic bias variable associated with bias of a measurement: update a state value set according to the measurements to yield an updated state value set; andpredict a next state value set in accordance with the updated state value set; anddetermine an orbit path of the target from the state value sets in real time. 16. The non-transitory computer readable medium of claim 15, the one or more bias variables comprising: a plurality of orientation bias variables associated with bias of an radar array orientation measurement; anda plurality of measurement bias variables associated with bias of a radar measurement. 17. The non-transitory computer readable medium of claim 15, wherein the computer code instructs the computer to: update the state value set by: updating the state value set and a covariance, the covariance correlating the measurement variables and the dynamic bias variables; andpredict the next state value set by: calculating the next state value set and a next covariance. 18. The non-transitory computer readable medium of claim 15, wherein the computer code further instructs the computer to: collect the radar measurements; andbatch filter the radar measurements to generate an initial state value set. 19. The non-transitory computer readable medium of claim 15, wherein the computer code instructs the computer to yield the plurality of state value sets by: calculating a measurement residual according to the radar measurements and the radar array orientation measurements. 20. The non-transitory computer readable medium of claim 15, wherein the computer code instructs the computer to update the state value set by: updating the state value set using a covariance that correlates the dynamic bias variables. 21. The non-transitory computer readable medium of claim 15, wherein the computer code instructs the computer to predict the next state value set by: predicting the next state value set using an orbital model configured to determine a next path point from a current path point.