The Automated Multimodal Trend Analysis System (AMTAS) developed at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center designed to monitor, diagnose, and resolve spacecraft health and safety trends. It consists of a state estimator and predictor, and a Discrete Event Reasoner. The estimator and predictor dynamically model a set of telemetry data, and predict their future trends. The DER consists of a hypothesis generator and resolver, and a simulator. The diagnostic algorithm is modelbased guided by an uncertainty handler. In this talk we discus a new development: an on-board Attitude Sensor Calibration (ASCAL), based on components developed for AMTAS. will focus on its hybrid system structure.