This one could interest you: An Introduction to the Kalman Filter (Authors: Greg Welch and Gary Bishop).

Thank you dear Alejandro, this is a book ? or a scientific paper ?

It's a course book. This is the link: 

http://www.cs.unc.edu/~tracker/media/pdf/SIGGRAPH2001_CoursePack_08.pdf

Although there is a paper with the same name and authors:

http://www.cs.yale.edu/homes/hudak-paul/CS474S01/kalman.pdf

For Python users this one  is also very interesting: Kalman and Bayesian Filters in Python.(Author: Roger R Labbe Jr) available in:

http://robotics.itee.uq.edu.au/~elec3004/2015/tutes/Kalman_and_Bayesian_Filters_in_Python.pdf

Thank you dear Alejandro, I have a question if it is possible, in which step the system is controlled by kalman filter, in "Time Update" step or in "Measurement Update " step ? 

Dear Saad:

I'm just learning Kalman Filter  right now, may be my answer is not the best.  As I understand when the Kalman Filter algorithm moves to a new time step, it makes a prediction of the state variable and covariance matrix for that time based on the already computed and updated (using the measurement and the Kalman gain) state variable for the previous time.  In the measurement update step  the  state variable and covariance matrix are  "improved" using the measurement, so is in this step were Kalman Filter adjusts its parameters in order to make the new prediction (it finds a Kalman gain that minimizes the a "posteriori" or the updated error covariance equation) I'm not sure if I answer your question.  You need to read the documentation about Kalman Filter.

Thank you alejandro