An improved Kalman Filter algorithm in the application of self-stabilization platform

As the self-stabilization platform is being used more and more widely in film shooting and artillery launching, the requirement of stability of the platform is increasing. This paper introduces an improved Kalman Filter algorithm, and this method uses Least Square method to do linear fitting the previous k-1 conditions, thus the prediction error is decreased in the traditional Kalman Filter algorithm. The results show that the shrinkage of the Kalman status can be decreased significantly, the variance of the measured angle and the deviation of measurement can be reduced, and the stability of the platform is increased.