Methods and systems automatically detect, classify and/or mitigate sensor errors using partial qualitative and quantitative knowledge of the subsystems. In various examples, sensor fault detection is performed with a custom designed representation scheme covering causality, correlation, system of equality and inequalities, and an associated logic. The logic is described by a set of algorithmic steps to iteratively assign trustworthiness level of sensors. Sensor fault classification is performed by combining mathematical and statistical techniques that can be utilized to expose bias, drift, multiplicative calibration error, precision degradation and spike error. Sensor fault mitigation is also performed on identified bias, drift, multiplicative calibration error, precision degradation and spike error.