This paper presents formulation and validation of an adaptive filter for real-time calibration of redundant signals consisting of sensor data and/or analytically derived measurements. The measurement noise covariance matrix is adjusted as a function of the a posteriori probabilities of failure of the individual signals. An estimate of the measured variable is obtained as a weighted average of the calibrated signals. The weighting matrix is recursively updated in real time instead of being fixed a priori. The calibration and estimation filter has been tested by injecting faults into the data set collected from an operating power plant. The filter software is presently hasted in a Pentium platform and is portable to other commercial platforms. The filter can be used to enhance the Instrumentation & Control System Software in tactical and transport aircraft, and nuclear and fossil power plants.