Improved performance evaluation of colored Kalman filter for a real-time case study

It has remained custom to analyze system with standard assumptions on noise. In this work, more realistic scenario has been considered by taking more general noise (colored) that is equally applicable to colored noise and Gaussian noise. A variable factor has been introduced that may switch between both the noise scenarios. Most of the estimation algorithms widely employed are inadequate in case of colored noise. To overcome this limitation, a modified Kalman filtering based estimation algorithm is proposed that processes a real-time data. In order to provide some of the promising results of our proposed observer, a real-time mass-spring damper system case study suffering from colored noise is provided. The simulation results validates the efficiency of proposed scheme wherein the aim is dealing with the estimation problems aroused due to colored noise.