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Hi, I was using kalman filter, where I need to call predict but at varying timesteps. I am referring to example where fixed delta t are used for state propagation. My measurement updates and predictions are async and can come at varying time intervals so first update can be called at 1s, next at 5s, and next at 6s... so on. from the source code it seems not doable as m ie. model is private and is fixed during initialization, now I can change A matrix(reflecting delta t multiplication) in model itself but this won't be reflected in kf object, as its pass by value, not pass by pointer. Can you please suggest, if there already exists something for this in library or a workaround.
The text was updated successfully, but these errors were encountered:
Hi, I was using kalman filter, where I need to call predict but at varying timesteps. I am referring to example where fixed delta t are used for state propagation. My measurement updates and predictions are async and can come at varying time intervals so first update can be called at 1s, next at 5s, and next at 6s... so on. from the source code it seems not doable as
m
ie. model is private and is fixed during initialization, now I can changeA
matrix(reflecting delta t multiplication) in model itself but this won't be reflected inkf
object, as its pass by value, not pass by pointer. Can you please suggest, if there already exists something for this in library or a workaround.The text was updated successfully, but these errors were encountered: