Two-frame random phase shifting interferometry based on constrained Kalman filter without pre-filtering

This paper discusses a phase estimation algorithm in two-frame phase-shifting interferometry using a con-strained Kalman filter without the need of pre-filtering operation for the background intensity removal. A state-space model is developed and state estimation is performed based on the extended Kalman filter. The Kalman smoother algorithm is utilized to improve the accuracy of state estimation. A comparative study is presented between the proposed and four state-of-art phase estimation methods. Both simulation and experimental results show good accuracy and noise robustness of the proposed method over a wide range of phase shifts.