Dear Muhammad Khan,

State is measured by using a sensor, to estimate state by estimator or filter like Kalman Filter; a real state is a state whose access is direct from the process.

Best regards

Dear all,

Let me expand the answer with an example. Consider for example the (Extended) Kalman Filter in your mobile phone responsible for providing you with the phone's location. The true state would be your actual position. The measurement could be for example a linearized pseudo-range measurement from a GPS satellite in a form of a 2D plane. The estimate of the state at the current time step would be then the position the Kalman Filter calculates based on the measurement(s) (and the predicted state estimate based on the state estimate of the previous time step). Hope this helps.

Best regards

Thanks dear

It really helpful

Thanks dear

It really helpful

I am using opencv and object detection, I want to know the location of an object in the next frame but measurement location and truestate location are equal, right? Is this a problem? Tommi Perälä Mohamed-Mourad Lafifi @

@Ufik Asil

Not really. Your object detection algorithm might (and always will) contain some errors.

So real and measured location of your object are not identical. And you want to predict the real location within the next frame. As an example of additional challenge - the object might be partially occluded ( in the measurement frame or in the predicted one).